tests/testthat/test_explore_time_series.R
In shane-kercheval/rtools: Package providing R tools and wrappers
context('Exploratory Analysis - Time Series')
library(testthat)
library(ggplot2)
library(dplyr)
options(dplyr.summarise.inform=F)
library(lubridate)
library(gapminder)
library(nycflights13)
library(forcats)
# library(scales)
source('test_helpers.R')
test_that('rt_explore_plot_time_series', {
dataset <- data.frame(flights %>%
mutate(date = lubridate::make_date(year, month, day),
cohort = paste0(year, '-',
lubridate::week(date)))) %>%
select(date, dep_delay, dep_time, origin, cohort)
colnames(dataset) <- test_helper__column_names(dataset)
variable <- 'Date Col'
comparison_variable <- 'Dep Delay Col'
comp_func_sum <- function(x) {
return (sum(x, na.rm=TRUE))
}
comp_func_mean <- function(x) {
return (mean(x, na.rm=TRUE))
}
comp_func_median <- function(x) {
return (median(x, na.rm=TRUE))
}
test_save_plot(file_name='data/rt_explore_plot_time_series_default.png',
plot=rt_explore_plot_time_series(dataset=dataset, variable=variable))
test_save_plot(file_name='data/rt_explore_plot_time_series_default_include_zero_false.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable, include_zero_y_axis = FALSE))
# rquires both comparison_function and comparison_function_name
expect_error(rt_explore_plot_time_series(dataset=dataset, variable=variable,
comparison_variable=comparison_variable))
expect_error(rt_explore_plot_time_series(dataset=dataset, variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_sum))
expect_error(rt_explore_plot_time_series(dataset=dataset, variable=variable,
comparison_variable=comparison_variable,
comparison_function_name='Sum'))
test_save_plot(file_name='data/rt_explore_plot_time_series_comparison_sum.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_sum,
comparison_function_name='Sum of'))
test_save_plot(file_name='data/rt_explore_plot_time_series_comparison_mean.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_mean,
comparison_function_name='Average'))
test_save_plot(file_name='data/rt_explore_plot_time_series_comparison_median.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_median,
comparison_function_name='Median'))
test_save_plot(file_name='data/rt_explore_plot_time_series_comparison_median_zoom_min.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_median,
comparison_function_name='Median',
y_zoom_min=0))
test_save_plot(file_name='data/rt_explore_plot_time_series_comparison_median_zoom_minmax.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_median,
comparison_function_name='Median',
y_zoom_min=0,
y_zoom_max=10,
base_size=15))
test_save_plot(file_name='data/rt_explore_plot_time_series_zoom_min.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
y_zoom_min=750,
base_size=15))
test_save_plot(file_name='data/rt_explore_plot_time_series_dep_time_zoom_min.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
comparison_variable='Dep Time Col',
comparison_function=comp_func_median,
comparison_function_name='Median',
y_zoom_min=1000,
y_zoom_max=NULL,
base_size=15))
color_variable <- 'Origin Col'
test_save_plot(file_name='data/rt_explore_plot_time_series_comparison_median_color.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_median,
comparison_function_name='Median',
color_variable = color_variable,
# y_zoom_min=0,
show_labels = TRUE,
y_zoom_max=25,
base_size=15))
test_save_plot(file_name='data/rt_explore_plot_time_series_count_color.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
color_variable=color_variable))
test_save_plot(file_name='data/rt_explore_plot_time_series_count_color_points_labels.png',
plot=rt_explore_plot_time_series(dataset=dataset %>% filter(month(`Date Col`) == 12),
variable=variable,
color_variable=color_variable,
show_points=TRUE,
show_labels=TRUE,
date_breaks = '1 day'))
})
test_that('rt_explore_plot_time_series__POSIXct', {
dataset <- data.frame(flights %>%
mutate(date = lubridate::make_date(year, month, day),
cohort = paste0(year, '-',
lubridate::week(date)))) %>%
select(date, dep_delay, dep_time, origin, cohort) %>%
mutate(date = as.POSIXct(date))
colnames(dataset) <- test_helper__column_names(dataset)
variable <- 'Date Col'
comparison_variable <- 'Dep Delay Col'
# was POSIXct failing
test_save_plot(file_name='data/rt_explore_plot_time_series_default__POSIXct.png',
plot=rt_explore_plot_time_series(dataset=dataset, variable=variable))
})
test_that('rt_as_year_qtr_format', {
expected_values <- c("2019-Q1", "", "", "", "2019-Q2", "", "", "2019-Q3", "", "", "2019-Q4", "", "", "", "2020-Q1", NA, "2019-Q1")
actual_values <- rt_as_year_qtr_format(c(ymd('2019-01-01',
'2019-01-02',
'2019-02-01',
'2019-03-04',
'2019-04-01',
'2019-04-04',
'2019-06-01',
'2019-07-01',
'2019-08-01',
'2019-09-01',
'2019-10-01',
'2019-11-01',
'2019-12-01',
'2019-12-31',
'2020-01-01',
NA,
'2019-01-01')))
expect_identical(expected_values, actual_values)
actual_values <- rt_as_year_qtr_format(as.POSIXct(c(ymd('2019-01-01',
'2019-01-02',
'2019-02-01',
'2019-03-04',
'2019-04-01',
'2019-04-04',
'2019-06-01',
'2019-07-01',
'2019-08-01',
'2019-09-01',
'2019-10-01',
'2019-11-01',
'2019-12-01',
'2019-12-31',
'2020-01-01',
NA,
'2019-01-01'))))
expect_identical(expected_values, actual_values)
})
test_that('rt_explore_plot_time_series_breaks_floors', {
dataset <- data.frame(flights %>%
mutate(date = lubridate::make_date(year, month, day),
cohort = paste0(year, '-',
lubridate::week(date)))) %>%
select(date, dep_delay, dep_time, origin, cohort)
colnames(dataset) <- test_helper__column_names(dataset)
variable <- 'Date Col'
comparison_variable <- 'Dep Delay Col'
comp_func_sum <- function(x) {
return (sum(x, na.rm=TRUE))
}
comp_func_mean <- function(x) {
return (mean(x, na.rm=TRUE))
}
comp_func_median <- function(x) {
return (median(x, na.rm=TRUE))
}
##########################################################################################################
# week/month/quarter/year defaults
##########################################################################################################
test_save_plot(file_name='data/rt_explore_plot_time_series_week.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'week',
date_break_format = NULL,
date_breaks_width = NULL))
test_save_plot(file_name='data/rt_explore_plot_time_series_month.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'month',
date_break_format = NULL,
date_breaks_width = NULL))
test_save_plot(file_name='data/rt_explore_plot_time_series_quarter.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'quarter',
date_break_format = NULL,
date_breaks_width = NULL))
test_save_plot(file_name='data/rt_explore_plot_time_series_year.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'year',
date_break_format = NULL,
date_breaks_width = NULL))
##########################################################################################################
# week/month/quarter/year widths
##########################################################################################################
test_save_plot(file_name='data/rt_explore_plot_time_series_week_width.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'week',
date_break_format = NULL,
date_breaks_width = '2 weeks'))
test_save_plot(file_name='data/rt_explore_plot_time_series_month_width.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'month',
date_break_format = NULL,
date_breaks_width = '4 months'))
test_save_plot(file_name='data/rt_explore_plot_time_series_quarter_width.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'quarter',
date_break_format = NULL,
date_breaks_width = '3 months'))
##########################################################################################################
# week/month/quarter/year formats
##########################################################################################################
test_save_plot(file_name='data/rt_explore_plot_time_series_week_format.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'week',
date_break_format = '%Y-%m-%d',
date_breaks_width = '2 weeks'))
test_save_plot(file_name='data/rt_explore_plot_time_series_month_format.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'month',
date_break_format = '%Y-%m-%d',
date_breaks_width = '4 months'))
test_save_plot(file_name='data/rt_explore_plot_time_series_quarter_format.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'quarter',
date_break_format = '%Y-%m-%d',
date_breaks_width = '3 months'))
##########################################################################################################
# week/month/quarter/year other variables & options
##########################################################################################################
test_save_plot(file_name='data/rt_explore_plot_time_series_sum_week.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_sum,
comparison_function_name='Sum of',
show_points = TRUE,
show_labels = TRUE,
date_floor = 'week'))
test_save_plot(file_name='data/rt_explore_plot_time_series_sum_month.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_sum,
comparison_function_name='Sum of',
show_points = TRUE,
show_labels = TRUE,
date_floor = 'month'))
test_save_plot(file_name='data/rt_explore_plot_time_series_sum_quarter.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_sum,
comparison_function_name='Sum of',
show_points = TRUE,
show_labels = TRUE,
date_floor = 'quarter'))
test_save_plot(file_name='data/rt_explore_plot_time_series_sum_year.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_sum,
comparison_function_name='Sum of',
show_points = TRUE,
show_labels = TRUE,
date_floor = 'year'))
test_save_plot(file_name='data/rt_explore_plot_time_series_average_week.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_mean,
comparison_function_name='Average',
show_points = TRUE,
show_labels = TRUE,
date_floor = 'week'))
test_save_plot(file_name='data/rt_explore_plot_time_series_average_month.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_mean,
comparison_function_name='Average',
show_points = TRUE,
show_labels = TRUE,
date_floor = 'month'))
test_save_plot(file_name='data/rt_explore_plot_time_series_average_quarter.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_mean,
comparison_function_name='Average',
show_points = TRUE,
show_labels = TRUE,
date_floor = 'quarter'))
test_save_plot(file_name='data/rt_explore_plot_time_series_average_year.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_mean,
comparison_function_name='Average',
show_points = TRUE,
show_labels = TRUE,
date_floor = 'year'))
test_save_plot(file_name='data/rt_explore_plot_time_series_median_week.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_median,
comparison_function_name='Median',
show_points = TRUE,
show_labels = TRUE,
date_floor = 'week'))
test_save_plot(file_name='data/rt_explore_plot_time_series_median_month.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_median,
comparison_function_name='Median',
show_points = TRUE,
show_labels = TRUE,
date_floor = 'month'))
test_save_plot(file_name='data/rt_explore_plot_time_series_median_quarter.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_median,
comparison_function_name='Median',
show_points = TRUE,
show_labels = TRUE,
date_floor = 'quarter'))
test_save_plot(file_name='data/rt_explore_plot_time_series_median_year.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_median,
comparison_function_name='Median',
show_points = TRUE,
show_labels = TRUE,
date_floor = 'year'))
##########################################################################################################
# week/month/quarter/year other variables & options
##########################################################################################################
color_variable <- 'Origin Col'
test_save_plot(file_name='data/rt_explore_plot_time_series_week_color.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
color_variable=color_variable,
show_points = TRUE,
show_labels = TRUE,
date_floor = 'week'))
test_save_plot(file_name='data/rt_explore_plot_time_series_average_week_color.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_mean,
comparison_function_name='Average',
color_variable = color_variable,
show_points = TRUE,
show_labels = TRUE,
date_floor = 'week'))
test_save_plot(file_name='data/rt_explore_plot_time_series_month_color.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
color_variable=color_variable,
show_points = TRUE,
show_labels = TRUE,
date_floor = 'month'))
test_save_plot(file_name='data/rt_explore_plot_time_series_average_month_color.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_mean,
comparison_function_name='Average',
color_variable = color_variable,
show_points = TRUE,
show_labels = TRUE,
date_floor = 'month'))
test_save_plot(file_name='data/rt_explore_plot_time_series_quarter_color.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
color_variable=color_variable,
show_points = TRUE,
show_labels = TRUE,
date_floor = 'quarter'))
test_save_plot(file_name='data/rt_explore_plot_time_series_average_quarter_color.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_mean,
comparison_function_name='Average',
color_variable = color_variable,
show_points = TRUE,
show_labels = TRUE,
date_floor = 'quarter'))
test_save_plot(file_name='data/rt_explore_plot_time_series_year_color.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
color_variable=color_variable,
show_points = TRUE,
show_labels = TRUE,
date_floor = 'year'))
test_save_plot(file_name='data/rt_explore_plot_time_series_average_year_color.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_mean,
comparison_function_name='Average',
color_variable = color_variable,
show_points = TRUE,
show_labels = TRUE,
date_floor = 'year'))
})
test_that('rt_explore_plot_time_series_breaks_floors_date_time', {
dataset_10 <- data.frame(flights) %>%
filter(floor_date(time_hour, unit = 'days') <= ymd('2013-02-10'))
dataset_11 <- data.frame(flights) %>%
filter(floor_date(time_hour, unit = 'days') <= ymd('2013-02-11'))
colnames(dataset_10) <- test_helper__column_names(dataset_10)
colnames(dataset_11) <- test_helper__column_names(dataset_11)
# max(dataset_10$time_hour)
# max(dataset_11$time_hour)
# dataset_11 %>%
# mutate(cohort = floor_date(time_hour, unit='weeks',week_start = 1)) %>%
# count(cohort)
variable <- 'Time Hour Col'
comparison_variable <- 'Dep Delay Col'
comp_func_sum <- function(x) {
return (sum(x, na.rm=TRUE))
}
comp_func_mean <- function(x) {
return (mean(x, na.rm=TRUE))
}
comp_func_median <- function(x) {
return (median(x, na.rm=TRUE))
}
##########################################################################################################
# week/month/quarter/year defaults
##########################################################################################################
test_save_plot(file_name='data/rt_explore_plot_time_series_datetime_week_210.png',
plot=rt_explore_plot_time_series(dataset=dataset_10,
variable=variable,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'week',
date_break_format = NULL,
date_breaks_width = NULL))
test_save_plot(file_name='data/rt_explore_plot_time_series_datetime_week_211.png',
plot=rt_explore_plot_time_series(dataset=dataset_11,
variable=variable,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'week',
date_break_format = NULL,
date_breaks_width = NULL))
test_save_plot(file_name='data/rt_explore_plot_time_series_datetime_week_210_day.png',
plot=rt_explore_plot_time_series(dataset=dataset_10,
variable=variable,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'week',
date_break_format = '%Y-%m-%d',
date_breaks_width = NULL))
test_save_plot(file_name='data/rt_explore_plot_time_series_datetime_week_211_day.png',
plot=rt_explore_plot_time_series(dataset=dataset_11,
variable=variable,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'week',
date_break_format = '%Y-%m-%d',
date_breaks_width = NULL))
##########################################################################################################
# week/month/quarter/year widths
##########################################################################################################
test_save_plot(file_name='data/rt_explore_plot_time_series_datetime_week_width_210.png',
plot=rt_explore_plot_time_series(dataset=dataset_10,
variable=variable,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'week',
date_break_format = NULL,
date_breaks_width = '2 weeks'))
test_save_plot(file_name='data/rt_explore_plot_time_series_datetime_week_width_211.png',
plot=rt_explore_plot_time_series(dataset=dataset_11,
variable=variable,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'week',
date_break_format = NULL,
date_breaks_width = '2 weeks'))
##########################################################################################################
# week/month/quarter/year formats
##########################################################################################################
test_save_plot(file_name='data/rt_explore_plot_time_series_datetime_week_format_210.png',
plot=rt_explore_plot_time_series(dataset=dataset_10,
variable=variable,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'week',
date_break_format = '%Y-%m-%d',
date_breaks_width = '2 weeks'))
test_save_plot(file_name='data/rt_explore_plot_time_series_datetime_week_format_211.png',
plot=rt_explore_plot_time_series(dataset=dataset_11,
variable=variable,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'week',
date_break_format = '%Y-%m-%d',
date_breaks_width = '2 weeks'))
##########################################################################################################
# week/month/quarter/year other variables & options
##########################################################################################################
test_save_plot(file_name='data/rt_explore_plot_time_series_datetime_sum_week_210.png',
plot=rt_explore_plot_time_series(dataset=dataset_10,
variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_sum,
comparison_function_name='Sum of',
show_points = TRUE,
show_labels = TRUE,
date_floor = 'week'))
test_save_plot(file_name='data/rt_explore_plot_time_series_datetime_sum_week_211.png',
plot=rt_explore_plot_time_series(dataset=dataset_11,
variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_sum,
comparison_function_name='Sum of',
show_points = TRUE,
show_labels = TRUE,
date_floor = 'week'))
})
test_that('rt_explore_plot_time_facet_yoy', {
# bike_traffic <- readr::read_csv("https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2019/2019-04-02/bike_traffic.csv")
# bike_traffic <- bike_traffic %>% mutate(date = mdy_hms(date))
dataset <- readRDS('data/bike_traffic.RDS')
set.seed(42)
dataset <- dataset %>% sample_n(10000)
dataset <- dataset %>% mutate(crossing = fct_lump(crossing, 1))
colnames(dataset) <- test_helper__column_names(dataset)
#dataset %>% count(crossing)
variable <- 'Date Col'
comparison_variable <- 'Bike Count Col'
comp_func_sum <- function(x) {
return (sum(x, na.rm=TRUE))
}
##########################################################################################################
# weekly
##########################################################################################################
##################
# Year-over-Year
##################
# use to verify numbers
# dataset %>%
# mutate(date = format_format('%Y-%W')(date)) %>%
# count(date) %>% arrange(date) %>% as.data.frame() %>% View()
test_save_plot(file_name='data/rt_explore_plot_time_series__yoy_week.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
year_over_year = TRUE,
facet_variable = NULL,
color_variable = NULL,
comparison_variable = NULL,
comparison_function = NULL,
comparison_function_name = NULL,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'week',
date_break_format = NULL,
date_breaks_width = '8 weeks'))
##################
# count
##################
test_save_plot(file_name='data/rt_explore_plot_time_series__facet_week.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
facet_variable = 'Direction Col',
color_variable = NULL,
comparison_variable = NULL,
comparison_function = NULL,
comparison_function_name = NULL,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'week',
date_break_format = NULL,
date_breaks_width = '8 weeks'))
# use to verify numbers
# dataset %>%
# mutate(date = format_format('%Y-%W')(date)) %>%
# count(date, direction) %>% arrange(direction, date) %>% as.data.frame() %>% View()
test_save_plot(file_name='data/rt_explore_plot_time_series__facet_week__yoy.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
facet_variable = 'Direction Col',
year_over_year = TRUE,
color_variable = NULL,
comparison_variable = NULL,
comparison_function = NULL,
comparison_function_name = NULL,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'week',
date_break_format = NULL,
date_breaks_width = '8 weeks'))
test_save_plot(file_name='data/rt_explore_plot_time_series__facet_color_week.png',
plot=rt_explore_plot_time_series(dataset=dataset %>%
mutate(`Direction Col` = fct_lump(`Direction Col`, 1)),
variable=variable,
facet_variable = 'Crossing Col',
color_variable = 'Direction Col',
comparison_variable = NULL,
comparison_function = NULL,
comparison_function_name = NULL,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'week',
date_break_format = '%Y-%m-%d',
date_breaks_width = '8 weeks'))
##################
# sum
##################
# use to verify numbers
# dataset %>%
# mutate(date = rt_floor_date_factor(date, 'week')) %>%
# count(date, direction, wt=bike_count) %>% arrange(direction, date) %>% as.data.frame() %>% head(40)
test_save_plot(file_name='data/rt_explore_plot_time_series__facet_week__sum.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
facet_variable = 'Direction Col',
color_variable = NULL,
comparison_variable = comparison_variable,
comparison_function = comp_func_sum,
comparison_function_name = 'SUM',
show_labels = TRUE,
show_points = TRUE,
date_floor = 'week',
date_break_format = NULL,
date_breaks_width = '8 weeks'))
# use to verify numbers
# dataset %>%
# mutate(date = format_format('%Y-%W')(date)) %>%
# count(date, direction, wt=bike_count) %>% arrange(direction, date) %>% as.data.frame() %>% View()
test_save_plot(file_name='data/rt_explore_plot_time_series__facet_week__sum__yoy.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
facet_variable = 'Direction Col',
year_over_year = TRUE,
color_variable = NULL,
comparison_variable = comparison_variable,
comparison_function = comp_func_sum,
comparison_function_name = 'SUM',
show_labels = TRUE,
show_points = TRUE,
date_floor = 'week',
date_break_format = NULL,
date_breaks_width = '8 weeks'))
# use to verify numbers
# dataset %>%
# mutate(date = rt_floor_date_factor(date, 'week')) %>%
# mutate(`Direction Col` = fct_lump(`Direction Col`, 1)) %>%
# count(date, crossing, direction, wt=bike_count) %>% arrange(crossing, direction, date) %>% as.data.frame() %>% View()
test_save_plot(file_name='data/rt_explore_plot_time_series__facet_color_week__sum.png',
plot=rt_explore_plot_time_series(dataset=dataset %>%
mutate(`Direction Col` = fct_lump(`Direction Col`, 1)),
variable=variable,
facet_variable = 'Crossing Col',
color_variable = 'Direction Col',
comparison_variable = comparison_variable,
comparison_function = comp_func_sum,
comparison_function_name = 'SUM',
show_labels = TRUE,
show_points = TRUE,
date_floor = 'week',
date_break_format = '%Y-%m-%d',
date_breaks_width = '8 weeks'))
##########################################################################################################
# monthly
##########################################################################################################
##################
# count
##################
# use to verify numbers
# dataset %>%
# mutate(date = rt_floor_date_factor(date, 'month')) %>%
# count(date, direction) %>% arrange(direction, date) %>% as.data.frame() %>% View()
test_save_plot(file_name='data/rt_explore_plot_time_series__facet_month.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
facet_variable = 'Direction Col',
color_variable = NULL,
comparison_variable = NULL,
comparison_function = NULL,
comparison_function_name = NULL,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'month',
date_break_format = NULL,
date_breaks_width = '2 months'))
# use to verify numbers
# dataset %>%
# mutate(date = rt_floor_date_factor(date, 'month')) %>%
# count(date, direction) %>% arrange(direction, date) %>% as.data.frame() %>% View()
test_save_plot(file_name='data/rt_explore_plot_time_series__facet_month__yoy.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
facet_variable = 'Direction Col',
year_over_year = TRUE,
color_variable = NULL,
comparison_variable = NULL,
comparison_function = NULL,
comparison_function_name = NULL,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'month',
date_break_format = NULL,
date_breaks_width = '2 months'))
# use to verify numbers
# dataset %>%
# mutate(date = rt_floor_date_factor(date, 'month')) %>%
# mutate(`Direction Col` = fct_lump(`Direction Col`, 1)) %>%
# count(date, crossing, direction) %>% arrange(crossing, direction, date) %>% as.data.frame() %>% View()
test_save_plot(file_name='data/rt_explore_plot_time_series__facet_color_month.png',
plot=rt_explore_plot_time_series(dataset=dataset %>%
mutate(`Direction Col` = fct_lump(`Direction Col`, 1)),
variable=variable,
facet_variable = 'Crossing Col',
color_variable = 'Direction Col',
comparison_variable = NULL,
comparison_function = NULL,
comparison_function_name = NULL,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'month',
date_break_format = '%Y-%m-%d',
date_breaks_width = '2 months'))
##################
# sum
##################
# use to verify numbers
# dataset %>%
# mutate(date = rt_floor_date_factor(date, 'month')) %>%
# count(date, direction, wt=bike_count) %>% arrange(direction, date) %>% as.data.frame() %>% View()
test_save_plot(file_name='data/rt_explore_plot_time_series__facet_month__sum.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
facet_variable = 'Direction Col',
color_variable = NULL,
comparison_variable = comparison_variable,
comparison_function = comp_func_sum,
comparison_function_name = 'SUM',
show_labels = TRUE,
show_points = TRUE,
date_floor = 'month',
date_break_format = NULL,
date_breaks_width = '2 months'))
# use to verify numbers
# dataset %>%
# mutate(date = rt_floor_date_factor(date, 'month')) %>%
# count(date, direction, wt=bike_count) %>% arrange(direction, date) %>% as.data.frame() %>% View()
test_save_plot(file_name='data/rt_explore_plot_time_series__facet_month__sum__yoy.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
facet_variable = 'Direction Col',
year_over_year = TRUE,
color_variable = NULL,
comparison_variable = comparison_variable,
comparison_function = comp_func_sum,
comparison_function_name = 'SUM',
show_labels = TRUE,
show_points = TRUE,
date_floor = 'month',
date_break_format = NULL,
date_breaks_width = '2 months'))
# use to verify numbers
# dataset %>%
# mutate(date = rt_floor_date_factor(date, 'month')) %>%
# mutate(`Direction Col` = fct_lump(`Direction Col`, 1)) %>%
# count(date, crossing, direction, wt=bike_count) %>% arrange(crossing, direction, date) %>% as.data.frame() %>% View()
test_save_plot(file_name='data/rt_explore_plot_time_series__facet_color_month__sum.png',
plot=rt_explore_plot_time_series(dataset=dataset %>%
mutate(`Direction Col` = fct_lump(`Direction Col`, 1)),
variable=variable,
facet_variable = 'Crossing Col',
color_variable = 'Direction Col',
comparison_variable = comparison_variable,
comparison_function = comp_func_sum,
comparison_function_name = 'SUM',
show_labels = TRUE,
show_points = TRUE,
date_floor = 'month',
date_break_format = '%Y-%m-%d',
date_breaks_width = '2 months'))
# to test include_zero_y_axis, lets make the numbers much higher than they are and make sure no values are 0
comp_func_custom <- function(x) {
x <- ifelse(x == 0, 100000, x * 10000)
x <- sum(x, na.rm=TRUE)
x <- ifelse(x > 30000000, 30000000, x)
x <- ifelse(x < 1000000, 1000000, x)
return (x)
}
test_save_plot(file_name='data/rt_explore_plot_time_series__facet_color_month__include_zero.png',
plot=rt_explore_plot_time_series(dataset=dataset %>%
mutate(`Direction Col` = fct_lump(`Direction Col`, 1)),
variable=variable,
facet_variable = 'Crossing Col',
color_variable = 'Direction Col',
include_zero_y_axis = FALSE,
comparison_variable = comparison_variable,
comparison_function = comp_func_custom,
comparison_function_name = 'Custom',
show_labels = TRUE,
show_points = TRUE,
date_floor = 'month',
date_break_format = '%Y-%m-%d',
date_breaks_width = '2 months'))
##########################################################################################################
# quarterly
##########################################################################################################
##################
# count
##################
# use to verify numbers
# dataset %>%
# mutate(date = rt_floor_date_factor(date, 'quarter')) %>%
# count(date, direction) %>% arrange(direction, date) %>% as.data.frame() %>% View()
test_save_plot(file_name='data/rt_explore_plot_time_series__facet_quarter.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
facet_variable = 'Direction Col',
color_variable = NULL,
comparison_variable = NULL,
comparison_function = NULL,
comparison_function_name = NULL,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'quarter',
date_break_format = NULL,
date_breaks_width = '2 quarters'))
# use to verify numbers
# dataset %>%
# mutate(date = rt_floor_date_factor(date, 'quarter')) %>%
# count(date, direction) %>% arrange(direction, date) %>% as.data.frame() %>% View()
test_save_plot(file_name='data/rt_explore_plot_time_series__facet_quarter__yoy.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
facet_variable = 'Direction Col',
year_over_year = TRUE,
color_variable = NULL,
comparison_variable = NULL,
comparison_function = NULL,
comparison_function_name = NULL,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'quarter',
date_break_format = NULL,
date_breaks_width = '2 quarters'))
# use to verify numbers
# dataset %>%
# mutate(date = rt_floor_date_factor(date, 'quarter')) %>%
# mutate(`Direction Col` = fct_lump(`Direction Col`, 1)) %>%
# count(date, crossing, direction) %>% arrange(crossing, direction, date) %>% as.data.frame() %>% View()
test_save_plot(file_name='data/rt_explore_plot_time_series__facet_color_quarter.png',
plot=rt_explore_plot_time_series(dataset=dataset %>%
mutate(`Direction Col` = fct_lump(`Direction Col`, 1)),
variable=variable,
facet_variable = 'Crossing Col',
color_variable = 'Direction Col',
comparison_variable = NULL,
comparison_function = NULL,
comparison_function_name = NULL,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'quarter',
date_break_format = '%Y-%m-%d',
date_breaks_width = '2 quarters'))
##################
# sum
##################
# use to verify numbers
# dataset %>%
# mutate(date = rt_floor_date_factor(date, 'quarter')) %>%
# count(date, direction, wt=bike_count) %>% arrange(direction, date) %>% as.data.frame() %>% View()
test_save_plot(file_name='data/rt_explore_plot_time_series__facet_quarter__sum.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
facet_variable = 'Direction Col',
color_variable = NULL,
comparison_variable = comparison_variable,
comparison_function = comp_func_sum,
comparison_function_name = 'SUM',
show_labels = TRUE,
show_points = TRUE,
date_floor = 'quarter',
date_break_format = NULL,
date_breaks_width = '2 quarters'))
# use to verify numbers
# dataset %>%
# mutate(date = rt_floor_date_factor(date, 'quarter')) %>%
# count(date, direction, wt=bike_count) %>% arrange(direction, date) %>% as.data.frame() %>% View()
test_save_plot(file_name='data/rt_explore_plot_time_series__facet_quarter__sum__yoy.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
facet_variable = 'Direction Col',
year_over_year = TRUE,
color_variable = NULL,
comparison_variable = comparison_variable,
comparison_function = comp_func_sum,
comparison_function_name = 'SUM',
show_labels = TRUE,
show_points = TRUE,
date_floor = 'quarter',
date_break_format = NULL,
date_breaks_width = '2 quarters'))
# use to verify numbers
# dataset %>%
# mutate(date = rt_floor_date_factor(date, 'quarter')) %>%
# mutate(`Direction Col` = fct_lump(`Direction Col`, 1)) %>%
# count(date, crossing, direction, wt=bike_count) %>% arrange(crossing, direction, date) %>% as.data.frame() %>% View()
test_save_plot(file_name='data/rt_explore_plot_time_series__facet_color_quarter__sum.png',
plot=rt_explore_plot_time_series(dataset=dataset %>%
mutate(`Direction Col` = fct_lump(`Direction Col`, 1)),
variable=variable,
facet_variable = 'Crossing Col',
color_variable = 'Direction Col',
comparison_variable = comparison_variable,
comparison_function = comp_func_sum,
comparison_function_name = 'SUM',
show_labels = TRUE,
show_points = TRUE,
date_floor = 'quarter',
date_break_format = '%Y-%m-%d',
date_breaks_width = '2 quarters'))
# to test include_zero_y_axis, lets make the numbers much higher than they are and make sure no values are 0
comp_func_custom <- function(x) {
x <- ifelse(x == 0, 100000, x * 10000)
x <- sum(x, na.rm=TRUE)
x <- ifelse(x > 30000000, 30000000, x)
x <- ifelse(x < 1000000, 1000000, x)
return (x)
}
test_save_plot(file_name='data/rt_explore_plot_time_series__facet_color_quarter__include_zero.png',
plot=rt_explore_plot_time_series(dataset=dataset %>%
mutate(`Direction Col` = fct_lump(`Direction Col`, 1)),
variable=variable,
facet_variable = 'Crossing Col',
color_variable = 'Direction Col',
include_zero_y_axis = FALSE,
comparison_variable = comparison_variable,
comparison_function = comp_func_custom,
comparison_function_name = 'Custom',
show_labels = TRUE,
show_points = TRUE,
date_floor = 'quarter',
date_break_format = '%Y-%m-%d',
date_breaks_width = '2 quarters'))
})
test_that('rt_explore_plot_time_series', {
dataset <- data.frame(flights %>%
mutate(date = lubridate::make_date(year, month, day),
cohort = paste0(year, '-',
lubridate::week(date)))) %>%
select(date, dep_delay, dep_time, origin, cohort) %>%
mutate(origin = factor(origin, levels = c("JFK", "LGA", "EWR"), ordered=TRUE))
colnames(dataset) <- test_helper__column_names(dataset)
variable <- 'Date Col'
comparison_variable <- 'Dep Delay Col'
comp_func_sum <- function(x) {
return (sum(x, na.rm=TRUE))
}
test_save_plot(file_name='data/rt_explore_plot_time_series__colors.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
color_variable='Origin Col'))
test_save_plot(file_name='data/rt_explore_plot_time_series__colors__comp.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
color_variable='Origin Col',
comparison_variable=comparison_variable,
comparison_function = comp_func_sum,
comparison_function_name = 'Sum'))
})
test_that('rt_explore_plot_time_series__many_nas', {
dataset <- data.frame(flights %>% mutate(date = lubridate::make_date(year, month, day))) %>%
select(date, dep_delay, dep_time, origin)
update_indexes <- which(dataset$date < ymd('2013-09-01'))
dataset$date[update_indexes] <- NA
colnames(dataset) <- test_helper__column_names(dataset)
variable <- 'Date Col'
color_variable <- 'Origin Col'
# if there are many NAs, it will mess up the count scale, and we can't plot them anyway
test_save_plot(file_name='data/rt_explore_plot_time_series__many_nas.png',
plot=rt_explore_plot_time_series(dataset,
variable = variable,
color_variable = NULL))
test_save_plot(file_name='data/rt_explore_plot_time_series__many_nas__color.png',
plot=rt_explore_plot_time_series(dataset,
variable = variable,
color_variable = color_variable))
})
test_that('rt_explore_plot_conversion_rates', {
sample_size <- 20000
conversion_rate <- 0.3
set.seed(42)
conversion_data <- data.frame(index=1:sample_size,
first_visit=ymd_hms('2019-01-01 00:00:00') +
days(round(runif(n=sample_size, min=0, max=600))) +
hours(round(runif(n=sample_size, min=0, max=23))) +
minutes(round(runif(n=sample_size, min=0, max=60))) +
seconds(round(runif(n=sample_size, min=0, max=60))))
set.seed(43)
conversion_data$converted <- as.logical(rbinom(n=sample_size, size=1, prob=conversion_rate))
colnames(conversion_data) <- test_helper__column_names(conversion_data)
get_rand_binom_num <- function(seed, max_num) {
set.seed(seed)
rbinom(1, max_num, 0.3)
}
get_rand_unif_num <- function(seed, max_num) {
set.seed(seed)
as.integer(round(runif(n=1, min=0, max=max_num)))
}
conversion_data$`Num Days Col` <- map_int(conversion_data$`Index Col`, ~ get_rand_binom_num(., 39))
conversion_data$`Num Hours Col` <- map_int(conversion_data$`Index Col`, ~ get_rand_unif_num(., 23))
conversion_data <- conversion_data %>%
mutate(`Conversion Date Col` = `First Visit Col` +
days(`Num Days Col`) +
hours(`Num Hours Col`)) %>%
select(-`Num Days Col`, -`Num Hours Col`)
conversion_data$`Conversion Date Col`[which(!conversion_data$`Converted Col`)] <- NA
conversion_data <- conversion_data %>% mutate(group=ifelse(`Index Col` %% 2 == 0, 'A', 'B'))
conversion_data <- conversion_data %>% select(-`Index Col`, -`Converted Col`)
mock_reference_date <- max(conversion_data$`First Visit Col`)
##########################################################################################################
# Non-Groups
##########################################################################################################
##########################################################################################################
test_save_plot(file_name='data/rt_explore_plot_conversion_rates__days_month.png',
plot=rt_explore_plot_conversion_rates(dataset=conversion_data,
first_date='First Visit Col',
second_date='Conversion Date Col',
reference_date=mock_reference_date,
snapshots=c(6, 7, 10, 14),
snapshot_units='days',
date_floor='month',
color_or_facet='color',
year_over_year=FALSE,
y_zoom_min=NULL,
y_zoom_max=NULL,
include_zero_y_axis=TRUE,
show_points=TRUE,
show_labels=TRUE,
date_break_format=NULL,
date_breaks_width=NULL))
# there was a bug where unique values were being removed (e.g. so duplicated First Visit Col's would be removed)
# so the above and below conversion rates, which should be (about) the same, were actually different
# the graphs won't actually be the same because by doing round_date we lose some precision on the date,
# and therefore the date-diff between the first-visit and the conversion-date, but they should be close
test_save_plot(file_name='data/rt_explore_plot_conversion_rates__days_month__floor_bug.png',
plot=rt_explore_plot_conversion_rates(dataset=conversion_data %>%
mutate(`First Visit Col` = round_date(`First Visit Col`, unit='days')),
first_date='First Visit Col',
second_date='Conversion Date Col',
reference_date=mock_reference_date,
snapshots=c(6, 7, 10, 14),
snapshot_units='days',
date_floor='month',
color_or_facet='color',
year_over_year=FALSE,
y_zoom_min=NULL,
y_zoom_max=NULL,
include_zero_y_axis=TRUE,
show_points=TRUE,
show_labels=TRUE,
date_break_format=NULL,
date_breaks_width=NULL))
##########################################################################################################
test_save_plot(file_name='data/rt_explore_plot_conversion_rates__days_month_facet.png',
plot=rt_explore_plot_conversion_rates(dataset=conversion_data,
first_date='First Visit Col',
second_date='Conversion Date Col',
reference_date=mock_reference_date,
snapshots=c(6, 7, 10, 14),
snapshot_units='days',
date_floor='month',
color_or_facet='facet',
year_over_year=FALSE,
y_zoom_min=NULL,
y_zoom_max=NULL,
include_zero_y_axis=TRUE,
show_points=TRUE,
show_labels=TRUE,
date_break_format=NULL,
date_breaks_width=NULL))
##########################################################################################################
test_save_plot(file_name='data/rt_explore_plot_conversion_rates__days_month_yoy.png',
plot=rt_explore_plot_conversion_rates(dataset=conversion_data,
first_date='First Visit Col',
second_date='Conversion Date Col',
reference_date=mock_reference_date,
snapshots=c(6, 7, 10, 14),
snapshot_units='days',
date_floor='month',
color_or_facet='facet',
year_over_year=TRUE,
y_zoom_min=NULL,
y_zoom_max=NULL,
include_zero_y_axis=FALSE,
show_points=TRUE,
show_labels=TRUE,
date_break_format=NULL,
date_breaks_width=NULL))
##########################################################################################################
test_save_plot(file_name='data/rt_explore_plot_conversion_rates__days_month_yoy_ignore_color.png',
plot=rt_explore_plot_conversion_rates(dataset=conversion_data,
first_date='First Visit Col',
second_date='Conversion Date Col',
reference_date=mock_reference_date,
snapshots=c(6, 7, 10, 14),
snapshot_units='days',
date_floor='month',
color_or_facet='color',
year_over_year=TRUE,
y_zoom_min=NULL,
y_zoom_max=NULL,
include_zero_y_axis=FALSE,
show_points=TRUE,
show_labels=TRUE,
date_break_format=NULL,
date_breaks_width=NULL))
##########################################################################################################
test_save_plot(file_name='data/rt_explore_plot_conversion_rates__2.png',
plot=rt_explore_plot_conversion_rates(dataset=conversion_data,
first_date='First Visit Col',
second_date='Conversion Date Col',
reference_date=mock_reference_date,
snapshots=c(7, 14, 21),
snapshot_units='days',
date_floor='month',
color_or_facet='facet',
year_over_year=TRUE,
y_zoom_min=NULL,
y_zoom_max=NULL,
include_zero_y_axis=FALSE,
show_points=TRUE,
show_labels=TRUE,
date_break_format=NULL,
date_breaks_width=NULL))
##########################################################################################################
test_save_plot(file_name='data/rt_explore_plot_conversion_rates__weeks_weeks.png',
plot=rt_explore_plot_conversion_rates(dataset=conversion_data,
first_date='First Visit Col',
second_date='Conversion Date Col',
reference_date=mock_reference_date,
snapshots=c(1, 2, 3),
snapshot_units='weeks',
date_floor='weeks',
color_or_facet='color',
year_over_year=FALSE,
y_zoom_min=NULL,
y_zoom_max=NULL,
include_zero_y_axis=TRUE,
show_points=TRUE,
show_labels=TRUE,
date_break_format=NULL,
date_breaks_width='4 weeks'))
test_save_plot(file_name='data/rt_explore_plot_conversion_rates__weeks_weeks2.png',
plot=rt_explore_plot_conversion_rates(dataset=conversion_data %>%
filter(`First Visit Col` >= ymd_hms('2020-01-01 00:00:00')),
first_date='First Visit Col',
second_date='Conversion Date Col',
reference_date=mock_reference_date,
snapshots=c(1, 2, 3),
snapshot_units='weeks',
date_floor='weeks',
color_or_facet='color',
year_over_year=FALSE,
y_zoom_min=NULL,
y_zoom_max=NULL,
include_zero_y_axis=TRUE,
show_points=TRUE,
show_labels=TRUE,
date_break_format='%Y-%m-%d'
#date_breaks_width='4 weeks'
))
##########################################################################################################
test_save_plot(file_name='data/rt_explore_plot_conversion_rates__weeks_weeks_facet.png',
plot=rt_explore_plot_conversion_rates(dataset=conversion_data,
first_date='First Visit Col',
second_date='Conversion Date Col',
reference_date=mock_reference_date,
snapshots=c(1, 2, 3),
snapshot_units='weeks',
date_floor='weeks',
color_or_facet='facet',
year_over_year=FALSE,
y_zoom_min=NULL,
y_zoom_max=NULL,
include_zero_y_axis=TRUE,
show_points=TRUE,
show_labels=TRUE,
date_break_format=NULL,
date_breaks_width='4 weeks'))
##########################################################################################################
test_save_plot(file_name='data/rt_explore_plot_conversion_rates__weeks_weeks_yoy.png',
plot=rt_explore_plot_conversion_rates(dataset=conversion_data,
first_date='First Visit Col',
second_date='Conversion Date Col',
reference_date=mock_reference_date,
snapshots=c(1, 2, 3),
snapshot_units='weeks',
date_floor='weeks',
color_or_facet='facet',
year_over_year=TRUE,
y_zoom_min=NULL,
y_zoom_max=NULL,
include_zero_y_axis=TRUE,
show_points=TRUE,
show_labels=TRUE,
date_break_format=NULL,
date_breaks_width='4 weeks'))
##########################################################################################################
test_save_plot(file_name='data/rt_explore_plot_conversion_rates__weeks_weeks_2.png',
plot=rt_explore_plot_conversion_rates(dataset=conversion_data,
first_date='First Visit Col',
second_date='Conversion Date Col',
reference_date=mock_reference_date,
snapshots=c(1, 2, 3),
snapshot_units='weeks',
date_floor='weeks',
color_or_facet='facet',
year_over_year=TRUE,
y_zoom_min=NULL,
y_zoom_max=NULL,
include_zero_y_axis=FALSE,
show_points=TRUE,
show_labels=TRUE,
date_break_format='%Y-%m-%d',
date_breaks_width='4 weeks'))
##########################################################################################################
# GROUPS
##########################################################################################################
##########################################################################################################
test_save_plot(file_name='data/rt_explore_plot_conversion_rates__days_month__groups.png',
plot=rt_explore_plot_conversion_rates(dataset=conversion_data,
first_date='First Visit Col',
second_date='Conversion Date Col',
group_variable='group',
reference_date=mock_reference_date,
snapshots=c(6, 7, 10, 14),
snapshot_units='days',
date_floor='month',
color_or_facet='color',
year_over_year=FALSE,
y_zoom_min=NULL,
y_zoom_max=NULL,
include_zero_y_axis=TRUE,
show_points=TRUE,
show_labels=TRUE,
date_break_format=NULL,
date_breaks_width=NULL))
# there was a bug where unique values were being removed (e.g. so duplicated First Visit Col's would be removed)
# so the above and below conversion rates, which should be (about) the same, were actually different
# the graphs won't actually be the same because by doing round_date we lose some precision on the date,
# and therefore the date-diff between the first-visit and the conversion-date, but they should be close
test_save_plot(file_name='data/rt_explore_plot_conversion_rates__days_month__groups__floor_bug.png',
plot=rt_explore_plot_conversion_rates(dataset=conversion_data %>%
mutate(`First Visit Col` = round_date(`First Visit Col`, unit='days')),
first_date='First Visit Col',
second_date='Conversion Date Col',
group_variable='group',
reference_date=mock_reference_date,
snapshots=c(6, 7, 10, 14),
snapshot_units='days',
date_floor='month',
color_or_facet='color',
year_over_year=FALSE,
y_zoom_min=NULL,
y_zoom_max=NULL,
include_zero_y_axis=TRUE,
show_points=TRUE,
show_labels=TRUE,
date_break_format=NULL,
date_breaks_width=NULL))
##########################################################################################################
test_save_plot(file_name='data/rt_explore_plot_conversion_rates__days_month_facet__groups.png',
plot=rt_explore_plot_conversion_rates(dataset=conversion_data,
first_date='First Visit Col',
second_date='Conversion Date Col',
group_variable='group',
reference_date=mock_reference_date,
snapshots=c(6, 7, 10, 14),
snapshot_units='days',
date_floor='month',
color_or_facet='facet',
year_over_year=FALSE,
y_zoom_min=NULL,
y_zoom_max=NULL,
include_zero_y_axis=FALSE,
show_points=TRUE,
show_labels=TRUE,
date_break_format=NULL,
date_breaks_width=NULL))
##########################################################################################################
expect_error(rt_explore_plot_conversion_rates(dataset=conversion_data,
first_date='First Visit Col',
second_date='Conversion Date Col',
group_variable='group',
reference_date=mock_reference_date,
snapshots=c(6, 7, 10, 14),
snapshot_units='days',
date_floor='month',
color_or_facet='facet',
year_over_year=TRUE,
y_zoom_min=NULL,
y_zoom_max=NULL,
include_zero_y_axis=FALSE,
show_points=TRUE,
show_labels=TRUE,
date_break_format=NULL,
date_breaks_width=NULL))
##########################################################################################################
test_save_plot(file_name='data/rt_explore_plot_conversion_rates__weeks_weeks__groups.png',
plot=rt_explore_plot_conversion_rates(dataset=conversion_data,
first_date='First Visit Col',
second_date='Conversion Date Col',
group_variable='group',
reference_date=mock_reference_date,
snapshots=c(1, 2, 3),
snapshot_units='weeks',
date_floor='weeks',
color_or_facet='color',
year_over_year=FALSE,
y_zoom_min=NULL,
y_zoom_max=NULL,
include_zero_y_axis=TRUE,
show_points=TRUE,
show_labels=TRUE,
date_break_format=NULL,
date_breaks_width='4 weeks'))
test_save_plot(file_name='data/rt_explore_plot_conversion_rates__weeks_weeks2__groups.png',
plot=rt_explore_plot_conversion_rates(dataset=conversion_data %>%
filter(`First Visit Col` >= ymd_hms('2020-01-01 00:00:00')),
first_date='First Visit Col',
second_date='Conversion Date Col',
group_variable='group',
reference_date=mock_reference_date,
snapshots=c(1, 2, 3),
snapshot_units='weeks',
date_floor='weeks',
color_or_facet='color',
year_over_year=FALSE,
y_zoom_min=NULL,
y_zoom_max=NULL,
include_zero_y_axis=TRUE,
show_points=TRUE,
show_labels=TRUE,
date_break_format='%Y-%m-%d'
#date_breaks_width='4 weeks'
))
##########################################################################################################
test_save_plot(file_name='data/rt_explore_plot_conversion_rates__weeks_weeks_facet__groups.png',
plot=rt_explore_plot_conversion_rates(dataset=conversion_data,
first_date='First Visit Col',
second_date='Conversion Date Col',
group_variable='group',
reference_date=mock_reference_date,
snapshots=c(1, 2, 3),
snapshot_units='weeks',
date_floor='weeks',
color_or_facet='facet',
year_over_year=FALSE,
y_zoom_min=NULL,
y_zoom_max=NULL,
include_zero_y_axis=TRUE,
show_points=TRUE,
show_labels=TRUE,
date_break_format=NULL,
date_breaks_width='4 weeks'))
})
test_that('rt_explore_plot_cohorted_adoption', {
sample_size <- 20000
conversion_rate <- 0.3
set.seed(42)
conversion_data <- data.frame(index=1:sample_size,
first_visit=ymd_hms('2019-01-01 00:00:00') +
days(round(runif(n=sample_size, min=0, max=600))) +
hours(round(runif(n=sample_size, min=0, max=23))) +
minutes(round(runif(n=sample_size, min=0, max=60))) +
seconds(round(runif(n=sample_size, min=0, max=60))))
set.seed(43)
conversion_data$converted <- as.logical(rbinom(n=sample_size, size=1, prob=conversion_rate))
colnames(conversion_data) <- test_helper__column_names(conversion_data)
get_rand_binom_num <- function(seed, max_num) {
set.seed(seed)
rbinom(1, max_num, 0.3)
}
get_rand_unif_num <- function(seed, max_num) {
set.seed(seed)
as.integer(round(runif(n=1, min=0, max=max_num)))
}
conversion_data$`Num Days Col` <- map_int(conversion_data$`Index Col`, ~ get_rand_binom_num(., 39))
conversion_data$`Num Hours Col` <- map_int(conversion_data$`Index Col`, ~ get_rand_unif_num(., 23))
conversion_data <- conversion_data %>%
mutate(`Conversion Date Col` = `First Visit Col` +
days(`Num Days Col`) +
hours(`Num Hours Col`)) %>%
select(-`Num Days Col`, -`Num Hours Col`)
conversion_data$`Conversion Date Col`[which(!conversion_data$`Converted Col`)] <- NA
conversion_data <- conversion_data %>% select(-`Index Col`, -`Converted Col`)
mock_reference_date <- max(conversion_data$`First Visit Col`)
test_save_plot(file_name='data/rt_explore_plot_cohorted_adoption__30_days_month.png',
plot=rt_explore_plot_cohorted_adoption(dataset=conversion_data,
first_date='First Visit Col',
second_date='Conversion Date Col',
reference_date=mock_reference_date,
last_n_cohorts=10,
n_units_after_first_date=30,
units='days',
date_floor='month',
y_zoom_min=NULL,
y_zoom_max=NULL,
include_zero_y_axis=TRUE,
show_points=FALSE,
show_labels=FALSE,
date_break_format=NULL,
base_size=11))
test_save_plot(file_name='data/rt_explore_plot_cohorted_adoption__30_days_month_options.png',
plot=rt_explore_plot_cohorted_adoption(dataset=conversion_data,
first_date='First Visit Col',
second_date='Conversion Date Col',
reference_date=mock_reference_date,
last_n_cohorts=10,
n_units_after_first_date=30,
units='days',
date_floor='month',
y_zoom_min=NULL,
y_zoom_max=0.30,
include_zero_y_axis=TRUE,
show_points=TRUE,
show_labels=TRUE,
date_break_format='%Y-%m-%d',
base_size=11))
test_save_plot(file_name='data/rt_explore_plot_cohorted_adoption__3_weeks_week.png',
plot=rt_explore_plot_cohorted_adoption(dataset=conversion_data,
first_date='First Visit Col',
second_date='Conversion Date Col',
reference_date=mock_reference_date,
last_n_cohorts=15,
n_units_after_first_date=3,
units='weeks',
date_floor='week',
y_zoom_min=NULL,
#y_zoom_max=0.30,
include_zero_y_axis=TRUE,
#show_points=TRUE,
#show_labels=TRUE,
#date_break_format='%Y-%m-%d',
base_size=11))
test_save_plot(file_name='data/rt_explore_plot_cohorted_adoption__3_weeks_month_options1.png',
plot=rt_explore_plot_cohorted_adoption(dataset=conversion_data,
first_date='First Visit Col',
second_date='Conversion Date Col',
reference_date=mock_reference_date,
last_n_cohorts=100,
n_units_after_first_date=4,
units='weeks',
date_floor='month',
y_zoom_min=NULL,
separated_colors=FALSE,
#y_zoom_max=0.30,
include_zero_y_axis=TRUE,
show_points=TRUE,
#show_labels=TRUE,
#date_break_format='%Y-%W',
base_size=11))
test_save_plot(file_name='data/rt_explore_plot_cohorted_adoption__3_weeks_month_options2.png',
plot=rt_explore_plot_cohorted_adoption(dataset=conversion_data,
first_date='First Visit Col',
second_date='Conversion Date Col',
reference_date=mock_reference_date,
last_n_cohorts=100,
n_units_after_first_date=4,
units='weeks',
date_floor='month',
y_zoom_min=NULL,
separated_colors=TRUE,
#y_zoom_max=0.30,
include_zero_y_axis=TRUE,
show_points=TRUE,
#show_labels=TRUE,
#date_break_format='%Y-%W',
base_size=11))
})
shane-kercheval/rtools documentation built on July 7, 2022, 8:31 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
context('Exploratory Analysis - Time Series')
library(testthat)
library(ggplot2)
library(dplyr)
options(dplyr.summarise.inform=F)
library(lubridate)
library(gapminder)
library(nycflights13)
library(forcats)
# library(scales)
source('test_helpers.R')
test_that('rt_explore_plot_time_series', {
dataset <- data.frame(flights %>%
mutate(date = lubridate::make_date(year, month, day),
cohort = paste0(year, '-',
lubridate::week(date)))) %>%
select(date, dep_delay, dep_time, origin, cohort)
colnames(dataset) <- test_helper__column_names(dataset)
variable <- 'Date Col'
comparison_variable <- 'Dep Delay Col'
comp_func_sum <- function(x) {
return (sum(x, na.rm=TRUE))
}
comp_func_mean <- function(x) {
return (mean(x, na.rm=TRUE))
}
comp_func_median <- function(x) {
return (median(x, na.rm=TRUE))
}
test_save_plot(file_name='data/rt_explore_plot_time_series_default.png',
plot=rt_explore_plot_time_series(dataset=dataset, variable=variable))
test_save_plot(file_name='data/rt_explore_plot_time_series_default_include_zero_false.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable, include_zero_y_axis = FALSE))
# rquires both comparison_function and comparison_function_name
expect_error(rt_explore_plot_time_series(dataset=dataset, variable=variable,
comparison_variable=comparison_variable))
expect_error(rt_explore_plot_time_series(dataset=dataset, variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_sum))
expect_error(rt_explore_plot_time_series(dataset=dataset, variable=variable,
comparison_variable=comparison_variable,
comparison_function_name='Sum'))
test_save_plot(file_name='data/rt_explore_plot_time_series_comparison_sum.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_sum,
comparison_function_name='Sum of'))
test_save_plot(file_name='data/rt_explore_plot_time_series_comparison_mean.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_mean,
comparison_function_name='Average'))
test_save_plot(file_name='data/rt_explore_plot_time_series_comparison_median.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_median,
comparison_function_name='Median'))
test_save_plot(file_name='data/rt_explore_plot_time_series_comparison_median_zoom_min.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_median,
comparison_function_name='Median',
y_zoom_min=0))
test_save_plot(file_name='data/rt_explore_plot_time_series_comparison_median_zoom_minmax.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_median,
comparison_function_name='Median',
y_zoom_min=0,
y_zoom_max=10,
base_size=15))
test_save_plot(file_name='data/rt_explore_plot_time_series_zoom_min.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
y_zoom_min=750,
base_size=15))
test_save_plot(file_name='data/rt_explore_plot_time_series_dep_time_zoom_min.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
comparison_variable='Dep Time Col',
comparison_function=comp_func_median,
comparison_function_name='Median',
y_zoom_min=1000,
y_zoom_max=NULL,
base_size=15))
color_variable <- 'Origin Col'
test_save_plot(file_name='data/rt_explore_plot_time_series_comparison_median_color.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_median,
comparison_function_name='Median',
color_variable = color_variable,
# y_zoom_min=0,
show_labels = TRUE,
y_zoom_max=25,
base_size=15))
test_save_plot(file_name='data/rt_explore_plot_time_series_count_color.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
color_variable=color_variable))
test_save_plot(file_name='data/rt_explore_plot_time_series_count_color_points_labels.png',
plot=rt_explore_plot_time_series(dataset=dataset %>% filter(month(`Date Col`) == 12),
variable=variable,
color_variable=color_variable,
show_points=TRUE,
show_labels=TRUE,
date_breaks = '1 day'))
})
test_that('rt_explore_plot_time_series__POSIXct', {
dataset <- data.frame(flights %>%
mutate(date = lubridate::make_date(year, month, day),
cohort = paste0(year, '-',
lubridate::week(date)))) %>%
select(date, dep_delay, dep_time, origin, cohort) %>%
mutate(date = as.POSIXct(date))
colnames(dataset) <- test_helper__column_names(dataset)
variable <- 'Date Col'
comparison_variable <- 'Dep Delay Col'
# was POSIXct failing
test_save_plot(file_name='data/rt_explore_plot_time_series_default__POSIXct.png',
plot=rt_explore_plot_time_series(dataset=dataset, variable=variable))
})
test_that('rt_as_year_qtr_format', {
expected_values <- c("2019-Q1", "", "", "", "2019-Q2", "", "", "2019-Q3", "", "", "2019-Q4", "", "", "", "2020-Q1", NA, "2019-Q1")
actual_values <- rt_as_year_qtr_format(c(ymd('2019-01-01',
'2019-01-02',
'2019-02-01',
'2019-03-04',
'2019-04-01',
'2019-04-04',
'2019-06-01',
'2019-07-01',
'2019-08-01',
'2019-09-01',
'2019-10-01',
'2019-11-01',
'2019-12-01',
'2019-12-31',
'2020-01-01',
NA,
'2019-01-01')))
expect_identical(expected_values, actual_values)
actual_values <- rt_as_year_qtr_format(as.POSIXct(c(ymd('2019-01-01',
'2019-01-02',
'2019-02-01',
'2019-03-04',
'2019-04-01',
'2019-04-04',
'2019-06-01',
'2019-07-01',
'2019-08-01',
'2019-09-01',
'2019-10-01',
'2019-11-01',
'2019-12-01',
'2019-12-31',
'2020-01-01',
NA,
'2019-01-01'))))
expect_identical(expected_values, actual_values)
})
test_that('rt_explore_plot_time_series_breaks_floors', {
dataset <- data.frame(flights %>%
mutate(date = lubridate::make_date(year, month, day),
cohort = paste0(year, '-',
lubridate::week(date)))) %>%
select(date, dep_delay, dep_time, origin, cohort)
colnames(dataset) <- test_helper__column_names(dataset)
variable <- 'Date Col'
comparison_variable <- 'Dep Delay Col'
comp_func_sum <- function(x) {
return (sum(x, na.rm=TRUE))
}
comp_func_mean <- function(x) {
return (mean(x, na.rm=TRUE))
}
comp_func_median <- function(x) {
return (median(x, na.rm=TRUE))
}
##########################################################################################################
# week/month/quarter/year defaults
##########################################################################################################
test_save_plot(file_name='data/rt_explore_plot_time_series_week.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'week',
date_break_format = NULL,
date_breaks_width = NULL))
test_save_plot(file_name='data/rt_explore_plot_time_series_month.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'month',
date_break_format = NULL,
date_breaks_width = NULL))
test_save_plot(file_name='data/rt_explore_plot_time_series_quarter.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'quarter',
date_break_format = NULL,
date_breaks_width = NULL))
test_save_plot(file_name='data/rt_explore_plot_time_series_year.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'year',
date_break_format = NULL,
date_breaks_width = NULL))
##########################################################################################################
# week/month/quarter/year widths
##########################################################################################################
test_save_plot(file_name='data/rt_explore_plot_time_series_week_width.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'week',
date_break_format = NULL,
date_breaks_width = '2 weeks'))
test_save_plot(file_name='data/rt_explore_plot_time_series_month_width.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'month',
date_break_format = NULL,
date_breaks_width = '4 months'))
test_save_plot(file_name='data/rt_explore_plot_time_series_quarter_width.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'quarter',
date_break_format = NULL,
date_breaks_width = '3 months'))
##########################################################################################################
# week/month/quarter/year formats
##########################################################################################################
test_save_plot(file_name='data/rt_explore_plot_time_series_week_format.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'week',
date_break_format = '%Y-%m-%d',
date_breaks_width = '2 weeks'))
test_save_plot(file_name='data/rt_explore_plot_time_series_month_format.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'month',
date_break_format = '%Y-%m-%d',
date_breaks_width = '4 months'))
test_save_plot(file_name='data/rt_explore_plot_time_series_quarter_format.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'quarter',
date_break_format = '%Y-%m-%d',
date_breaks_width = '3 months'))
##########################################################################################################
# week/month/quarter/year other variables & options
##########################################################################################################
test_save_plot(file_name='data/rt_explore_plot_time_series_sum_week.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_sum,
comparison_function_name='Sum of',
show_points = TRUE,
show_labels = TRUE,
date_floor = 'week'))
test_save_plot(file_name='data/rt_explore_plot_time_series_sum_month.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_sum,
comparison_function_name='Sum of',
show_points = TRUE,
show_labels = TRUE,
date_floor = 'month'))
test_save_plot(file_name='data/rt_explore_plot_time_series_sum_quarter.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_sum,
comparison_function_name='Sum of',
show_points = TRUE,
show_labels = TRUE,
date_floor = 'quarter'))
test_save_plot(file_name='data/rt_explore_plot_time_series_sum_year.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_sum,
comparison_function_name='Sum of',
show_points = TRUE,
show_labels = TRUE,
date_floor = 'year'))
test_save_plot(file_name='data/rt_explore_plot_time_series_average_week.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_mean,
comparison_function_name='Average',
show_points = TRUE,
show_labels = TRUE,
date_floor = 'week'))
test_save_plot(file_name='data/rt_explore_plot_time_series_average_month.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_mean,
comparison_function_name='Average',
show_points = TRUE,
show_labels = TRUE,
date_floor = 'month'))
test_save_plot(file_name='data/rt_explore_plot_time_series_average_quarter.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_mean,
comparison_function_name='Average',
show_points = TRUE,
show_labels = TRUE,
date_floor = 'quarter'))
test_save_plot(file_name='data/rt_explore_plot_time_series_average_year.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_mean,
comparison_function_name='Average',
show_points = TRUE,
show_labels = TRUE,
date_floor = 'year'))
test_save_plot(file_name='data/rt_explore_plot_time_series_median_week.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_median,
comparison_function_name='Median',
show_points = TRUE,
show_labels = TRUE,
date_floor = 'week'))
test_save_plot(file_name='data/rt_explore_plot_time_series_median_month.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_median,
comparison_function_name='Median',
show_points = TRUE,
show_labels = TRUE,
date_floor = 'month'))
test_save_plot(file_name='data/rt_explore_plot_time_series_median_quarter.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_median,
comparison_function_name='Median',
show_points = TRUE,
show_labels = TRUE,
date_floor = 'quarter'))
test_save_plot(file_name='data/rt_explore_plot_time_series_median_year.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_median,
comparison_function_name='Median',
show_points = TRUE,
show_labels = TRUE,
date_floor = 'year'))
##########################################################################################################
# week/month/quarter/year other variables & options
##########################################################################################################
color_variable <- 'Origin Col'
test_save_plot(file_name='data/rt_explore_plot_time_series_week_color.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
color_variable=color_variable,
show_points = TRUE,
show_labels = TRUE,
date_floor = 'week'))
test_save_plot(file_name='data/rt_explore_plot_time_series_average_week_color.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_mean,
comparison_function_name='Average',
color_variable = color_variable,
show_points = TRUE,
show_labels = TRUE,
date_floor = 'week'))
test_save_plot(file_name='data/rt_explore_plot_time_series_month_color.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
color_variable=color_variable,
show_points = TRUE,
show_labels = TRUE,
date_floor = 'month'))
test_save_plot(file_name='data/rt_explore_plot_time_series_average_month_color.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_mean,
comparison_function_name='Average',
color_variable = color_variable,
show_points = TRUE,
show_labels = TRUE,
date_floor = 'month'))
test_save_plot(file_name='data/rt_explore_plot_time_series_quarter_color.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
color_variable=color_variable,
show_points = TRUE,
show_labels = TRUE,
date_floor = 'quarter'))
test_save_plot(file_name='data/rt_explore_plot_time_series_average_quarter_color.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_mean,
comparison_function_name='Average',
color_variable = color_variable,
show_points = TRUE,
show_labels = TRUE,
date_floor = 'quarter'))
test_save_plot(file_name='data/rt_explore_plot_time_series_year_color.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
color_variable=color_variable,
show_points = TRUE,
show_labels = TRUE,
date_floor = 'year'))
test_save_plot(file_name='data/rt_explore_plot_time_series_average_year_color.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_mean,
comparison_function_name='Average',
color_variable = color_variable,
show_points = TRUE,
show_labels = TRUE,
date_floor = 'year'))
})
test_that('rt_explore_plot_time_series_breaks_floors_date_time', {
dataset_10 <- data.frame(flights) %>%
filter(floor_date(time_hour, unit = 'days') <= ymd('2013-02-10'))
dataset_11 <- data.frame(flights) %>%
filter(floor_date(time_hour, unit = 'days') <= ymd('2013-02-11'))
colnames(dataset_10) <- test_helper__column_names(dataset_10)
colnames(dataset_11) <- test_helper__column_names(dataset_11)
# max(dataset_10$time_hour)
# max(dataset_11$time_hour)
# dataset_11 %>%
# mutate(cohort = floor_date(time_hour, unit='weeks',week_start = 1)) %>%
# count(cohort)
variable <- 'Time Hour Col'
comparison_variable <- 'Dep Delay Col'
comp_func_sum <- function(x) {
return (sum(x, na.rm=TRUE))
}
comp_func_mean <- function(x) {
return (mean(x, na.rm=TRUE))
}
comp_func_median <- function(x) {
return (median(x, na.rm=TRUE))
}
##########################################################################################################
# week/month/quarter/year defaults
##########################################################################################################
test_save_plot(file_name='data/rt_explore_plot_time_series_datetime_week_210.png',
plot=rt_explore_plot_time_series(dataset=dataset_10,
variable=variable,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'week',
date_break_format = NULL,
date_breaks_width = NULL))
test_save_plot(file_name='data/rt_explore_plot_time_series_datetime_week_211.png',
plot=rt_explore_plot_time_series(dataset=dataset_11,
variable=variable,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'week',
date_break_format = NULL,
date_breaks_width = NULL))
test_save_plot(file_name='data/rt_explore_plot_time_series_datetime_week_210_day.png',
plot=rt_explore_plot_time_series(dataset=dataset_10,
variable=variable,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'week',
date_break_format = '%Y-%m-%d',
date_breaks_width = NULL))
test_save_plot(file_name='data/rt_explore_plot_time_series_datetime_week_211_day.png',
plot=rt_explore_plot_time_series(dataset=dataset_11,
variable=variable,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'week',
date_break_format = '%Y-%m-%d',
date_breaks_width = NULL))
##########################################################################################################
# week/month/quarter/year widths
##########################################################################################################
test_save_plot(file_name='data/rt_explore_plot_time_series_datetime_week_width_210.png',
plot=rt_explore_plot_time_series(dataset=dataset_10,
variable=variable,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'week',
date_break_format = NULL,
date_breaks_width = '2 weeks'))
test_save_plot(file_name='data/rt_explore_plot_time_series_datetime_week_width_211.png',
plot=rt_explore_plot_time_series(dataset=dataset_11,
variable=variable,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'week',
date_break_format = NULL,
date_breaks_width = '2 weeks'))
##########################################################################################################
# week/month/quarter/year formats
##########################################################################################################
test_save_plot(file_name='data/rt_explore_plot_time_series_datetime_week_format_210.png',
plot=rt_explore_plot_time_series(dataset=dataset_10,
variable=variable,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'week',
date_break_format = '%Y-%m-%d',
date_breaks_width = '2 weeks'))
test_save_plot(file_name='data/rt_explore_plot_time_series_datetime_week_format_211.png',
plot=rt_explore_plot_time_series(dataset=dataset_11,
variable=variable,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'week',
date_break_format = '%Y-%m-%d',
date_breaks_width = '2 weeks'))
##########################################################################################################
# week/month/quarter/year other variables & options
##########################################################################################################
test_save_plot(file_name='data/rt_explore_plot_time_series_datetime_sum_week_210.png',
plot=rt_explore_plot_time_series(dataset=dataset_10,
variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_sum,
comparison_function_name='Sum of',
show_points = TRUE,
show_labels = TRUE,
date_floor = 'week'))
test_save_plot(file_name='data/rt_explore_plot_time_series_datetime_sum_week_211.png',
plot=rt_explore_plot_time_series(dataset=dataset_11,
variable=variable,
comparison_variable=comparison_variable,
comparison_function=comp_func_sum,
comparison_function_name='Sum of',
show_points = TRUE,
show_labels = TRUE,
date_floor = 'week'))
})
test_that('rt_explore_plot_time_facet_yoy', {
# bike_traffic <- readr::read_csv("https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2019/2019-04-02/bike_traffic.csv")
# bike_traffic <- bike_traffic %>% mutate(date = mdy_hms(date))
dataset <- readRDS('data/bike_traffic.RDS')
set.seed(42)
dataset <- dataset %>% sample_n(10000)
dataset <- dataset %>% mutate(crossing = fct_lump(crossing, 1))
colnames(dataset) <- test_helper__column_names(dataset)
#dataset %>% count(crossing)
variable <- 'Date Col'
comparison_variable <- 'Bike Count Col'
comp_func_sum <- function(x) {
return (sum(x, na.rm=TRUE))
}
##########################################################################################################
# weekly
##########################################################################################################
##################
# Year-over-Year
##################
# use to verify numbers
# dataset %>%
# mutate(date = format_format('%Y-%W')(date)) %>%
# count(date) %>% arrange(date) %>% as.data.frame() %>% View()
test_save_plot(file_name='data/rt_explore_plot_time_series__yoy_week.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
year_over_year = TRUE,
facet_variable = NULL,
color_variable = NULL,
comparison_variable = NULL,
comparison_function = NULL,
comparison_function_name = NULL,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'week',
date_break_format = NULL,
date_breaks_width = '8 weeks'))
##################
# count
##################
test_save_plot(file_name='data/rt_explore_plot_time_series__facet_week.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
facet_variable = 'Direction Col',
color_variable = NULL,
comparison_variable = NULL,
comparison_function = NULL,
comparison_function_name = NULL,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'week',
date_break_format = NULL,
date_breaks_width = '8 weeks'))
# use to verify numbers
# dataset %>%
# mutate(date = format_format('%Y-%W')(date)) %>%
# count(date, direction) %>% arrange(direction, date) %>% as.data.frame() %>% View()
test_save_plot(file_name='data/rt_explore_plot_time_series__facet_week__yoy.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
facet_variable = 'Direction Col',
year_over_year = TRUE,
color_variable = NULL,
comparison_variable = NULL,
comparison_function = NULL,
comparison_function_name = NULL,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'week',
date_break_format = NULL,
date_breaks_width = '8 weeks'))
test_save_plot(file_name='data/rt_explore_plot_time_series__facet_color_week.png',
plot=rt_explore_plot_time_series(dataset=dataset %>%
mutate(`Direction Col` = fct_lump(`Direction Col`, 1)),
variable=variable,
facet_variable = 'Crossing Col',
color_variable = 'Direction Col',
comparison_variable = NULL,
comparison_function = NULL,
comparison_function_name = NULL,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'week',
date_break_format = '%Y-%m-%d',
date_breaks_width = '8 weeks'))
##################
# sum
##################
# use to verify numbers
# dataset %>%
# mutate(date = rt_floor_date_factor(date, 'week')) %>%
# count(date, direction, wt=bike_count) %>% arrange(direction, date) %>% as.data.frame() %>% head(40)
test_save_plot(file_name='data/rt_explore_plot_time_series__facet_week__sum.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
facet_variable = 'Direction Col',
color_variable = NULL,
comparison_variable = comparison_variable,
comparison_function = comp_func_sum,
comparison_function_name = 'SUM',
show_labels = TRUE,
show_points = TRUE,
date_floor = 'week',
date_break_format = NULL,
date_breaks_width = '8 weeks'))
# use to verify numbers
# dataset %>%
# mutate(date = format_format('%Y-%W')(date)) %>%
# count(date, direction, wt=bike_count) %>% arrange(direction, date) %>% as.data.frame() %>% View()
test_save_plot(file_name='data/rt_explore_plot_time_series__facet_week__sum__yoy.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
facet_variable = 'Direction Col',
year_over_year = TRUE,
color_variable = NULL,
comparison_variable = comparison_variable,
comparison_function = comp_func_sum,
comparison_function_name = 'SUM',
show_labels = TRUE,
show_points = TRUE,
date_floor = 'week',
date_break_format = NULL,
date_breaks_width = '8 weeks'))
# use to verify numbers
# dataset %>%
# mutate(date = rt_floor_date_factor(date, 'week')) %>%
# mutate(`Direction Col` = fct_lump(`Direction Col`, 1)) %>%
# count(date, crossing, direction, wt=bike_count) %>% arrange(crossing, direction, date) %>% as.data.frame() %>% View()
test_save_plot(file_name='data/rt_explore_plot_time_series__facet_color_week__sum.png',
plot=rt_explore_plot_time_series(dataset=dataset %>%
mutate(`Direction Col` = fct_lump(`Direction Col`, 1)),
variable=variable,
facet_variable = 'Crossing Col',
color_variable = 'Direction Col',
comparison_variable = comparison_variable,
comparison_function = comp_func_sum,
comparison_function_name = 'SUM',
show_labels = TRUE,
show_points = TRUE,
date_floor = 'week',
date_break_format = '%Y-%m-%d',
date_breaks_width = '8 weeks'))
##########################################################################################################
# monthly
##########################################################################################################
##################
# count
##################
# use to verify numbers
# dataset %>%
# mutate(date = rt_floor_date_factor(date, 'month')) %>%
# count(date, direction) %>% arrange(direction, date) %>% as.data.frame() %>% View()
test_save_plot(file_name='data/rt_explore_plot_time_series__facet_month.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
facet_variable = 'Direction Col',
color_variable = NULL,
comparison_variable = NULL,
comparison_function = NULL,
comparison_function_name = NULL,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'month',
date_break_format = NULL,
date_breaks_width = '2 months'))
# use to verify numbers
# dataset %>%
# mutate(date = rt_floor_date_factor(date, 'month')) %>%
# count(date, direction) %>% arrange(direction, date) %>% as.data.frame() %>% View()
test_save_plot(file_name='data/rt_explore_plot_time_series__facet_month__yoy.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
facet_variable = 'Direction Col',
year_over_year = TRUE,
color_variable = NULL,
comparison_variable = NULL,
comparison_function = NULL,
comparison_function_name = NULL,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'month',
date_break_format = NULL,
date_breaks_width = '2 months'))
# use to verify numbers
# dataset %>%
# mutate(date = rt_floor_date_factor(date, 'month')) %>%
# mutate(`Direction Col` = fct_lump(`Direction Col`, 1)) %>%
# count(date, crossing, direction) %>% arrange(crossing, direction, date) %>% as.data.frame() %>% View()
test_save_plot(file_name='data/rt_explore_plot_time_series__facet_color_month.png',
plot=rt_explore_plot_time_series(dataset=dataset %>%
mutate(`Direction Col` = fct_lump(`Direction Col`, 1)),
variable=variable,
facet_variable = 'Crossing Col',
color_variable = 'Direction Col',
comparison_variable = NULL,
comparison_function = NULL,
comparison_function_name = NULL,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'month',
date_break_format = '%Y-%m-%d',
date_breaks_width = '2 months'))
##################
# sum
##################
# use to verify numbers
# dataset %>%
# mutate(date = rt_floor_date_factor(date, 'month')) %>%
# count(date, direction, wt=bike_count) %>% arrange(direction, date) %>% as.data.frame() %>% View()
test_save_plot(file_name='data/rt_explore_plot_time_series__facet_month__sum.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
facet_variable = 'Direction Col',
color_variable = NULL,
comparison_variable = comparison_variable,
comparison_function = comp_func_sum,
comparison_function_name = 'SUM',
show_labels = TRUE,
show_points = TRUE,
date_floor = 'month',
date_break_format = NULL,
date_breaks_width = '2 months'))
# use to verify numbers
# dataset %>%
# mutate(date = rt_floor_date_factor(date, 'month')) %>%
# count(date, direction, wt=bike_count) %>% arrange(direction, date) %>% as.data.frame() %>% View()
test_save_plot(file_name='data/rt_explore_plot_time_series__facet_month__sum__yoy.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
facet_variable = 'Direction Col',
year_over_year = TRUE,
color_variable = NULL,
comparison_variable = comparison_variable,
comparison_function = comp_func_sum,
comparison_function_name = 'SUM',
show_labels = TRUE,
show_points = TRUE,
date_floor = 'month',
date_break_format = NULL,
date_breaks_width = '2 months'))
# use to verify numbers
# dataset %>%
# mutate(date = rt_floor_date_factor(date, 'month')) %>%
# mutate(`Direction Col` = fct_lump(`Direction Col`, 1)) %>%
# count(date, crossing, direction, wt=bike_count) %>% arrange(crossing, direction, date) %>% as.data.frame() %>% View()
test_save_plot(file_name='data/rt_explore_plot_time_series__facet_color_month__sum.png',
plot=rt_explore_plot_time_series(dataset=dataset %>%
mutate(`Direction Col` = fct_lump(`Direction Col`, 1)),
variable=variable,
facet_variable = 'Crossing Col',
color_variable = 'Direction Col',
comparison_variable = comparison_variable,
comparison_function = comp_func_sum,
comparison_function_name = 'SUM',
show_labels = TRUE,
show_points = TRUE,
date_floor = 'month',
date_break_format = '%Y-%m-%d',
date_breaks_width = '2 months'))
# to test include_zero_y_axis, lets make the numbers much higher than they are and make sure no values are 0
comp_func_custom <- function(x) {
x <- ifelse(x == 0, 100000, x * 10000)
x <- sum(x, na.rm=TRUE)
x <- ifelse(x > 30000000, 30000000, x)
x <- ifelse(x < 1000000, 1000000, x)
return (x)
}
test_save_plot(file_name='data/rt_explore_plot_time_series__facet_color_month__include_zero.png',
plot=rt_explore_plot_time_series(dataset=dataset %>%
mutate(`Direction Col` = fct_lump(`Direction Col`, 1)),
variable=variable,
facet_variable = 'Crossing Col',
color_variable = 'Direction Col',
include_zero_y_axis = FALSE,
comparison_variable = comparison_variable,
comparison_function = comp_func_custom,
comparison_function_name = 'Custom',
show_labels = TRUE,
show_points = TRUE,
date_floor = 'month',
date_break_format = '%Y-%m-%d',
date_breaks_width = '2 months'))
##########################################################################################################
# quarterly
##########################################################################################################
##################
# count
##################
# use to verify numbers
# dataset %>%
# mutate(date = rt_floor_date_factor(date, 'quarter')) %>%
# count(date, direction) %>% arrange(direction, date) %>% as.data.frame() %>% View()
test_save_plot(file_name='data/rt_explore_plot_time_series__facet_quarter.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
facet_variable = 'Direction Col',
color_variable = NULL,
comparison_variable = NULL,
comparison_function = NULL,
comparison_function_name = NULL,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'quarter',
date_break_format = NULL,
date_breaks_width = '2 quarters'))
# use to verify numbers
# dataset %>%
# mutate(date = rt_floor_date_factor(date, 'quarter')) %>%
# count(date, direction) %>% arrange(direction, date) %>% as.data.frame() %>% View()
test_save_plot(file_name='data/rt_explore_plot_time_series__facet_quarter__yoy.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
facet_variable = 'Direction Col',
year_over_year = TRUE,
color_variable = NULL,
comparison_variable = NULL,
comparison_function = NULL,
comparison_function_name = NULL,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'quarter',
date_break_format = NULL,
date_breaks_width = '2 quarters'))
# use to verify numbers
# dataset %>%
# mutate(date = rt_floor_date_factor(date, 'quarter')) %>%
# mutate(`Direction Col` = fct_lump(`Direction Col`, 1)) %>%
# count(date, crossing, direction) %>% arrange(crossing, direction, date) %>% as.data.frame() %>% View()
test_save_plot(file_name='data/rt_explore_plot_time_series__facet_color_quarter.png',
plot=rt_explore_plot_time_series(dataset=dataset %>%
mutate(`Direction Col` = fct_lump(`Direction Col`, 1)),
variable=variable,
facet_variable = 'Crossing Col',
color_variable = 'Direction Col',
comparison_variable = NULL,
comparison_function = NULL,
comparison_function_name = NULL,
show_labels = TRUE,
show_points = TRUE,
date_floor = 'quarter',
date_break_format = '%Y-%m-%d',
date_breaks_width = '2 quarters'))
##################
# sum
##################
# use to verify numbers
# dataset %>%
# mutate(date = rt_floor_date_factor(date, 'quarter')) %>%
# count(date, direction, wt=bike_count) %>% arrange(direction, date) %>% as.data.frame() %>% View()
test_save_plot(file_name='data/rt_explore_plot_time_series__facet_quarter__sum.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
facet_variable = 'Direction Col',
color_variable = NULL,
comparison_variable = comparison_variable,
comparison_function = comp_func_sum,
comparison_function_name = 'SUM',
show_labels = TRUE,
show_points = TRUE,
date_floor = 'quarter',
date_break_format = NULL,
date_breaks_width = '2 quarters'))
# use to verify numbers
# dataset %>%
# mutate(date = rt_floor_date_factor(date, 'quarter')) %>%
# count(date, direction, wt=bike_count) %>% arrange(direction, date) %>% as.data.frame() %>% View()
test_save_plot(file_name='data/rt_explore_plot_time_series__facet_quarter__sum__yoy.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
facet_variable = 'Direction Col',
year_over_year = TRUE,
color_variable = NULL,
comparison_variable = comparison_variable,
comparison_function = comp_func_sum,
comparison_function_name = 'SUM',
show_labels = TRUE,
show_points = TRUE,
date_floor = 'quarter',
date_break_format = NULL,
date_breaks_width = '2 quarters'))
# use to verify numbers
# dataset %>%
# mutate(date = rt_floor_date_factor(date, 'quarter')) %>%
# mutate(`Direction Col` = fct_lump(`Direction Col`, 1)) %>%
# count(date, crossing, direction, wt=bike_count) %>% arrange(crossing, direction, date) %>% as.data.frame() %>% View()
test_save_plot(file_name='data/rt_explore_plot_time_series__facet_color_quarter__sum.png',
plot=rt_explore_plot_time_series(dataset=dataset %>%
mutate(`Direction Col` = fct_lump(`Direction Col`, 1)),
variable=variable,
facet_variable = 'Crossing Col',
color_variable = 'Direction Col',
comparison_variable = comparison_variable,
comparison_function = comp_func_sum,
comparison_function_name = 'SUM',
show_labels = TRUE,
show_points = TRUE,
date_floor = 'quarter',
date_break_format = '%Y-%m-%d',
date_breaks_width = '2 quarters'))
# to test include_zero_y_axis, lets make the numbers much higher than they are and make sure no values are 0
comp_func_custom <- function(x) {
x <- ifelse(x == 0, 100000, x * 10000)
x <- sum(x, na.rm=TRUE)
x <- ifelse(x > 30000000, 30000000, x)
x <- ifelse(x < 1000000, 1000000, x)
return (x)
}
test_save_plot(file_name='data/rt_explore_plot_time_series__facet_color_quarter__include_zero.png',
plot=rt_explore_plot_time_series(dataset=dataset %>%
mutate(`Direction Col` = fct_lump(`Direction Col`, 1)),
variable=variable,
facet_variable = 'Crossing Col',
color_variable = 'Direction Col',
include_zero_y_axis = FALSE,
comparison_variable = comparison_variable,
comparison_function = comp_func_custom,
comparison_function_name = 'Custom',
show_labels = TRUE,
show_points = TRUE,
date_floor = 'quarter',
date_break_format = '%Y-%m-%d',
date_breaks_width = '2 quarters'))
})
test_that('rt_explore_plot_time_series', {
dataset <- data.frame(flights %>%
mutate(date = lubridate::make_date(year, month, day),
cohort = paste0(year, '-',
lubridate::week(date)))) %>%
select(date, dep_delay, dep_time, origin, cohort) %>%
mutate(origin = factor(origin, levels = c("JFK", "LGA", "EWR"), ordered=TRUE))
colnames(dataset) <- test_helper__column_names(dataset)
variable <- 'Date Col'
comparison_variable <- 'Dep Delay Col'
comp_func_sum <- function(x) {
return (sum(x, na.rm=TRUE))
}
test_save_plot(file_name='data/rt_explore_plot_time_series__colors.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
color_variable='Origin Col'))
test_save_plot(file_name='data/rt_explore_plot_time_series__colors__comp.png',
plot=rt_explore_plot_time_series(dataset=dataset,
variable=variable,
color_variable='Origin Col',
comparison_variable=comparison_variable,
comparison_function = comp_func_sum,
comparison_function_name = 'Sum'))
})
test_that('rt_explore_plot_time_series__many_nas', {
dataset <- data.frame(flights %>% mutate(date = lubridate::make_date(year, month, day))) %>%
select(date, dep_delay, dep_time, origin)
update_indexes <- which(dataset$date < ymd('2013-09-01'))
dataset$date[update_indexes] <- NA
colnames(dataset) <- test_helper__column_names(dataset)
variable <- 'Date Col'
color_variable <- 'Origin Col'
# if there are many NAs, it will mess up the count scale, and we can't plot them anyway
test_save_plot(file_name='data/rt_explore_plot_time_series__many_nas.png',
plot=rt_explore_plot_time_series(dataset,
variable = variable,
color_variable = NULL))
test_save_plot(file_name='data/rt_explore_plot_time_series__many_nas__color.png',
plot=rt_explore_plot_time_series(dataset,
variable = variable,
color_variable = color_variable))
})
test_that('rt_explore_plot_conversion_rates', {
sample_size <- 20000
conversion_rate <- 0.3
set.seed(42)
conversion_data <- data.frame(index=1:sample_size,
first_visit=ymd_hms('2019-01-01 00:00:00') +
days(round(runif(n=sample_size, min=0, max=600))) +
hours(round(runif(n=sample_size, min=0, max=23))) +
minutes(round(runif(n=sample_size, min=0, max=60))) +
seconds(round(runif(n=sample_size, min=0, max=60))))
set.seed(43)
conversion_data$converted <- as.logical(rbinom(n=sample_size, size=1, prob=conversion_rate))
colnames(conversion_data) <- test_helper__column_names(conversion_data)
get_rand_binom_num <- function(seed, max_num) {
set.seed(seed)
rbinom(1, max_num, 0.3)
}
get_rand_unif_num <- function(seed, max_num) {
set.seed(seed)
as.integer(round(runif(n=1, min=0, max=max_num)))
}
conversion_data$`Num Days Col` <- map_int(conversion_data$`Index Col`, ~ get_rand_binom_num(., 39))
conversion_data$`Num Hours Col` <- map_int(conversion_data$`Index Col`, ~ get_rand_unif_num(., 23))
conversion_data <- conversion_data %>%
mutate(`Conversion Date Col` = `First Visit Col` +
days(`Num Days Col`) +
hours(`Num Hours Col`)) %>%
select(-`Num Days Col`, -`Num Hours Col`)
conversion_data$`Conversion Date Col`[which(!conversion_data$`Converted Col`)] <- NA
conversion_data <- conversion_data %>% mutate(group=ifelse(`Index Col` %% 2 == 0, 'A', 'B'))
conversion_data <- conversion_data %>% select(-`Index Col`, -`Converted Col`)
mock_reference_date <- max(conversion_data$`First Visit Col`)
##########################################################################################################
# Non-Groups
##########################################################################################################
##########################################################################################################
test_save_plot(file_name='data/rt_explore_plot_conversion_rates__days_month.png',
plot=rt_explore_plot_conversion_rates(dataset=conversion_data,
first_date='First Visit Col',
second_date='Conversion Date Col',
reference_date=mock_reference_date,
snapshots=c(6, 7, 10, 14),
snapshot_units='days',
date_floor='month',
color_or_facet='color',
year_over_year=FALSE,
y_zoom_min=NULL,
y_zoom_max=NULL,
include_zero_y_axis=TRUE,
show_points=TRUE,
show_labels=TRUE,
date_break_format=NULL,
date_breaks_width=NULL))
# there was a bug where unique values were being removed (e.g. so duplicated First Visit Col's would be removed)
# so the above and below conversion rates, which should be (about) the same, were actually different
# the graphs won't actually be the same because by doing round_date we lose some precision on the date,
# and therefore the date-diff between the first-visit and the conversion-date, but they should be close
test_save_plot(file_name='data/rt_explore_plot_conversion_rates__days_month__floor_bug.png',
plot=rt_explore_plot_conversion_rates(dataset=conversion_data %>%
mutate(`First Visit Col` = round_date(`First Visit Col`, unit='days')),
first_date='First Visit Col',
second_date='Conversion Date Col',
reference_date=mock_reference_date,
snapshots=c(6, 7, 10, 14),
snapshot_units='days',
date_floor='month',
color_or_facet='color',
year_over_year=FALSE,
y_zoom_min=NULL,
y_zoom_max=NULL,
include_zero_y_axis=TRUE,
show_points=TRUE,
show_labels=TRUE,
date_break_format=NULL,
date_breaks_width=NULL))
##########################################################################################################
test_save_plot(file_name='data/rt_explore_plot_conversion_rates__days_month_facet.png',
plot=rt_explore_plot_conversion_rates(dataset=conversion_data,
first_date='First Visit Col',
second_date='Conversion Date Col',
reference_date=mock_reference_date,
snapshots=c(6, 7, 10, 14),
snapshot_units='days',
date_floor='month',
color_or_facet='facet',
year_over_year=FALSE,
y_zoom_min=NULL,
y_zoom_max=NULL,
include_zero_y_axis=TRUE,
show_points=TRUE,
show_labels=TRUE,
date_break_format=NULL,
date_breaks_width=NULL))
##########################################################################################################
test_save_plot(file_name='data/rt_explore_plot_conversion_rates__days_month_yoy.png',
plot=rt_explore_plot_conversion_rates(dataset=conversion_data,
first_date='First Visit Col',
second_date='Conversion Date Col',
reference_date=mock_reference_date,
snapshots=c(6, 7, 10, 14),
snapshot_units='days',
date_floor='month',
color_or_facet='facet',
year_over_year=TRUE,
y_zoom_min=NULL,
y_zoom_max=NULL,
include_zero_y_axis=FALSE,
show_points=TRUE,
show_labels=TRUE,
date_break_format=NULL,
date_breaks_width=NULL))
##########################################################################################################
test_save_plot(file_name='data/rt_explore_plot_conversion_rates__days_month_yoy_ignore_color.png',
plot=rt_explore_plot_conversion_rates(dataset=conversion_data,
first_date='First Visit Col',
second_date='Conversion Date Col',
reference_date=mock_reference_date,
snapshots=c(6, 7, 10, 14),
snapshot_units='days',
date_floor='month',
color_or_facet='color',
year_over_year=TRUE,
y_zoom_min=NULL,
y_zoom_max=NULL,
include_zero_y_axis=FALSE,
show_points=TRUE,
show_labels=TRUE,
date_break_format=NULL,
date_breaks_width=NULL))
##########################################################################################################
test_save_plot(file_name='data/rt_explore_plot_conversion_rates__2.png',
plot=rt_explore_plot_conversion_rates(dataset=conversion_data,
first_date='First Visit Col',
second_date='Conversion Date Col',
reference_date=mock_reference_date,
snapshots=c(7, 14, 21),
snapshot_units='days',
date_floor='month',
color_or_facet='facet',
year_over_year=TRUE,
y_zoom_min=NULL,
y_zoom_max=NULL,
include_zero_y_axis=FALSE,
show_points=TRUE,
show_labels=TRUE,
date_break_format=NULL,
date_breaks_width=NULL))
##########################################################################################################
test_save_plot(file_name='data/rt_explore_plot_conversion_rates__weeks_weeks.png',
plot=rt_explore_plot_conversion_rates(dataset=conversion_data,
first_date='First Visit Col',
second_date='Conversion Date Col',
reference_date=mock_reference_date,
snapshots=c(1, 2, 3),
snapshot_units='weeks',
date_floor='weeks',
color_or_facet='color',
year_over_year=FALSE,
y_zoom_min=NULL,
y_zoom_max=NULL,
include_zero_y_axis=TRUE,
show_points=TRUE,
show_labels=TRUE,
date_break_format=NULL,
date_breaks_width='4 weeks'))
test_save_plot(file_name='data/rt_explore_plot_conversion_rates__weeks_weeks2.png',
plot=rt_explore_plot_conversion_rates(dataset=conversion_data %>%
filter(`First Visit Col` >= ymd_hms('2020-01-01 00:00:00')),
first_date='First Visit Col',
second_date='Conversion Date Col',
reference_date=mock_reference_date,
snapshots=c(1, 2, 3),
snapshot_units='weeks',
date_floor='weeks',
color_or_facet='color',
year_over_year=FALSE,
y_zoom_min=NULL,
y_zoom_max=NULL,
include_zero_y_axis=TRUE,
show_points=TRUE,
show_labels=TRUE,
date_break_format='%Y-%m-%d'
#date_breaks_width='4 weeks'
))
##########################################################################################################
test_save_plot(file_name='data/rt_explore_plot_conversion_rates__weeks_weeks_facet.png',
plot=rt_explore_plot_conversion_rates(dataset=conversion_data,
first_date='First Visit Col',
second_date='Conversion Date Col',
reference_date=mock_reference_date,
snapshots=c(1, 2, 3),
snapshot_units='weeks',
date_floor='weeks',
color_or_facet='facet',
year_over_year=FALSE,
y_zoom_min=NULL,
y_zoom_max=NULL,
include_zero_y_axis=TRUE,
show_points=TRUE,
show_labels=TRUE,
date_break_format=NULL,
date_breaks_width='4 weeks'))
##########################################################################################################
test_save_plot(file_name='data/rt_explore_plot_conversion_rates__weeks_weeks_yoy.png',
plot=rt_explore_plot_conversion_rates(dataset=conversion_data,
first_date='First Visit Col',
second_date='Conversion Date Col',
reference_date=mock_reference_date,
snapshots=c(1, 2, 3),
snapshot_units='weeks',
date_floor='weeks',
color_or_facet='facet',
year_over_year=TRUE,
y_zoom_min=NULL,
y_zoom_max=NULL,
include_zero_y_axis=TRUE,
show_points=TRUE,
show_labels=TRUE,
date_break_format=NULL,
date_breaks_width='4 weeks'))
##########################################################################################################
test_save_plot(file_name='data/rt_explore_plot_conversion_rates__weeks_weeks_2.png',
plot=rt_explore_plot_conversion_rates(dataset=conversion_data,
first_date='First Visit Col',
second_date='Conversion Date Col',
reference_date=mock_reference_date,
snapshots=c(1, 2, 3),
snapshot_units='weeks',
date_floor='weeks',
color_or_facet='facet',
year_over_year=TRUE,
y_zoom_min=NULL,
y_zoom_max=NULL,
include_zero_y_axis=FALSE,
show_points=TRUE,
show_labels=TRUE,
date_break_format='%Y-%m-%d',
date_breaks_width='4 weeks'))
##########################################################################################################
# GROUPS
##########################################################################################################
##########################################################################################################
test_save_plot(file_name='data/rt_explore_plot_conversion_rates__days_month__groups.png',
plot=rt_explore_plot_conversion_rates(dataset=conversion_data,
first_date='First Visit Col',
second_date='Conversion Date Col',
group_variable='group',
reference_date=mock_reference_date,
snapshots=c(6, 7, 10, 14),
snapshot_units='days',
date_floor='month',
color_or_facet='color',
year_over_year=FALSE,
y_zoom_min=NULL,
y_zoom_max=NULL,
include_zero_y_axis=TRUE,
show_points=TRUE,
show_labels=TRUE,
date_break_format=NULL,
date_breaks_width=NULL))
# there was a bug where unique values were being removed (e.g. so duplicated First Visit Col's would be removed)
# so the above and below conversion rates, which should be (about) the same, were actually different
# the graphs won't actually be the same because by doing round_date we lose some precision on the date,
# and therefore the date-diff between the first-visit and the conversion-date, but they should be close
test_save_plot(file_name='data/rt_explore_plot_conversion_rates__days_month__groups__floor_bug.png',
plot=rt_explore_plot_conversion_rates(dataset=conversion_data %>%
mutate(`First Visit Col` = round_date(`First Visit Col`, unit='days')),
first_date='First Visit Col',
second_date='Conversion Date Col',
group_variable='group',
reference_date=mock_reference_date,
snapshots=c(6, 7, 10, 14),
snapshot_units='days',
date_floor='month',
color_or_facet='color',
year_over_year=FALSE,
y_zoom_min=NULL,
y_zoom_max=NULL,
include_zero_y_axis=TRUE,
show_points=TRUE,
show_labels=TRUE,
date_break_format=NULL,
date_breaks_width=NULL))
##########################################################################################################
test_save_plot(file_name='data/rt_explore_plot_conversion_rates__days_month_facet__groups.png',
plot=rt_explore_plot_conversion_rates(dataset=conversion_data,
first_date='First Visit Col',
second_date='Conversion Date Col',
group_variable='group',
reference_date=mock_reference_date,
snapshots=c(6, 7, 10, 14),
snapshot_units='days',
date_floor='month',
color_or_facet='facet',
year_over_year=FALSE,
y_zoom_min=NULL,
y_zoom_max=NULL,
include_zero_y_axis=FALSE,
show_points=TRUE,
show_labels=TRUE,
date_break_format=NULL,
date_breaks_width=NULL))
##########################################################################################################
expect_error(rt_explore_plot_conversion_rates(dataset=conversion_data,
first_date='First Visit Col',
second_date='Conversion Date Col',
group_variable='group',
reference_date=mock_reference_date,
snapshots=c(6, 7, 10, 14),
snapshot_units='days',
date_floor='month',
color_or_facet='facet',
year_over_year=TRUE,
y_zoom_min=NULL,
y_zoom_max=NULL,
include_zero_y_axis=FALSE,
show_points=TRUE,
show_labels=TRUE,
date_break_format=NULL,
date_breaks_width=NULL))
##########################################################################################################
test_save_plot(file_name='data/rt_explore_plot_conversion_rates__weeks_weeks__groups.png',
plot=rt_explore_plot_conversion_rates(dataset=conversion_data,
first_date='First Visit Col',
second_date='Conversion Date Col',
group_variable='group',
reference_date=mock_reference_date,
snapshots=c(1, 2, 3),
snapshot_units='weeks',
date_floor='weeks',
color_or_facet='color',
year_over_year=FALSE,
y_zoom_min=NULL,
y_zoom_max=NULL,
include_zero_y_axis=TRUE,
show_points=TRUE,
show_labels=TRUE,
date_break_format=NULL,
date_breaks_width='4 weeks'))
test_save_plot(file_name='data/rt_explore_plot_conversion_rates__weeks_weeks2__groups.png',
plot=rt_explore_plot_conversion_rates(dataset=conversion_data %>%
filter(`First Visit Col` >= ymd_hms('2020-01-01 00:00:00')),
first_date='First Visit Col',
second_date='Conversion Date Col',
group_variable='group',
reference_date=mock_reference_date,
snapshots=c(1, 2, 3),
snapshot_units='weeks',
date_floor='weeks',
color_or_facet='color',
year_over_year=FALSE,
y_zoom_min=NULL,
y_zoom_max=NULL,
include_zero_y_axis=TRUE,
show_points=TRUE,
show_labels=TRUE,
date_break_format='%Y-%m-%d'
#date_breaks_width='4 weeks'
))
##########################################################################################################
test_save_plot(file_name='data/rt_explore_plot_conversion_rates__weeks_weeks_facet__groups.png',
plot=rt_explore_plot_conversion_rates(dataset=conversion_data,
first_date='First Visit Col',
second_date='Conversion Date Col',
group_variable='group',
reference_date=mock_reference_date,
snapshots=c(1, 2, 3),
snapshot_units='weeks',
date_floor='weeks',
color_or_facet='facet',
year_over_year=FALSE,
y_zoom_min=NULL,
y_zoom_max=NULL,
include_zero_y_axis=TRUE,
show_points=TRUE,
show_labels=TRUE,
date_break_format=NULL,
date_breaks_width='4 weeks'))
})
test_that('rt_explore_plot_cohorted_adoption', {
sample_size <- 20000
conversion_rate <- 0.3
set.seed(42)
conversion_data <- data.frame(index=1:sample_size,
first_visit=ymd_hms('2019-01-01 00:00:00') +
days(round(runif(n=sample_size, min=0, max=600))) +
hours(round(runif(n=sample_size, min=0, max=23))) +
minutes(round(runif(n=sample_size, min=0, max=60))) +
seconds(round(runif(n=sample_size, min=0, max=60))))
set.seed(43)
conversion_data$converted <- as.logical(rbinom(n=sample_size, size=1, prob=conversion_rate))
colnames(conversion_data) <- test_helper__column_names(conversion_data)
get_rand_binom_num <- function(seed, max_num) {
set.seed(seed)
rbinom(1, max_num, 0.3)
}
get_rand_unif_num <- function(seed, max_num) {
set.seed(seed)
as.integer(round(runif(n=1, min=0, max=max_num)))
}
conversion_data$`Num Days Col` <- map_int(conversion_data$`Index Col`, ~ get_rand_binom_num(., 39))
conversion_data$`Num Hours Col` <- map_int(conversion_data$`Index Col`, ~ get_rand_unif_num(., 23))
conversion_data <- conversion_data %>%
mutate(`Conversion Date Col` = `First Visit Col` +
days(`Num Days Col`) +
hours(`Num Hours Col`)) %>%
select(-`Num Days Col`, -`Num Hours Col`)
conversion_data$`Conversion Date Col`[which(!conversion_data$`Converted Col`)] <- NA
conversion_data <- conversion_data %>% select(-`Index Col`, -`Converted Col`)
mock_reference_date <- max(conversion_data$`First Visit Col`)
test_save_plot(file_name='data/rt_explore_plot_cohorted_adoption__30_days_month.png',
plot=rt_explore_plot_cohorted_adoption(dataset=conversion_data,
first_date='First Visit Col',
second_date='Conversion Date Col',
reference_date=mock_reference_date,
last_n_cohorts=10,
n_units_after_first_date=30,
units='days',
date_floor='month',
y_zoom_min=NULL,
y_zoom_max=NULL,
include_zero_y_axis=TRUE,
show_points=FALSE,
show_labels=FALSE,
date_break_format=NULL,
base_size=11))
test_save_plot(file_name='data/rt_explore_plot_cohorted_adoption__30_days_month_options.png',
plot=rt_explore_plot_cohorted_adoption(dataset=conversion_data,
first_date='First Visit Col',
second_date='Conversion Date Col',
reference_date=mock_reference_date,
last_n_cohorts=10,
n_units_after_first_date=30,
units='days',
date_floor='month',
y_zoom_min=NULL,
y_zoom_max=0.30,
include_zero_y_axis=TRUE,
show_points=TRUE,
show_labels=TRUE,
date_break_format='%Y-%m-%d',
base_size=11))
test_save_plot(file_name='data/rt_explore_plot_cohorted_adoption__3_weeks_week.png',
plot=rt_explore_plot_cohorted_adoption(dataset=conversion_data,
first_date='First Visit Col',
second_date='Conversion Date Col',
reference_date=mock_reference_date,
last_n_cohorts=15,
n_units_after_first_date=3,
units='weeks',
date_floor='week',
y_zoom_min=NULL,
#y_zoom_max=0.30,
include_zero_y_axis=TRUE,
#show_points=TRUE,
#show_labels=TRUE,
#date_break_format='%Y-%m-%d',
base_size=11))
test_save_plot(file_name='data/rt_explore_plot_cohorted_adoption__3_weeks_month_options1.png',
plot=rt_explore_plot_cohorted_adoption(dataset=conversion_data,
first_date='First Visit Col',
second_date='Conversion Date Col',
reference_date=mock_reference_date,
last_n_cohorts=100,
n_units_after_first_date=4,
units='weeks',
date_floor='month',
y_zoom_min=NULL,
separated_colors=FALSE,
#y_zoom_max=0.30,
include_zero_y_axis=TRUE,
show_points=TRUE,
#show_labels=TRUE,
#date_break_format='%Y-%W',
base_size=11))
test_save_plot(file_name='data/rt_explore_plot_cohorted_adoption__3_weeks_month_options2.png',
plot=rt_explore_plot_cohorted_adoption(dataset=conversion_data,
first_date='First Visit Col',
second_date='Conversion Date Col',
reference_date=mock_reference_date,
last_n_cohorts=100,
n_units_after_first_date=4,
units='weeks',
date_floor='month',
y_zoom_min=NULL,
separated_colors=TRUE,
#y_zoom_max=0.30,
include_zero_y_axis=TRUE,
show_points=TRUE,
#show_labels=TRUE,
#date_break_format='%Y-%W',
base_size=11))
})
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.